1 Introduction

Language plays a central role in persuasion. Small differences at phonological, lexical, syntactic, and discourse levels have been shown to impact the outcome of persuasive communication (Hosman, Reference Hosman, Dillard and Shen2012; Niebuhr & Barbosa, this volume). To date, a large body of research has documented the effects of linguistic choices on how persuasive messages are understood, processed, and ultimately complied with (cf., among others, Xiao et al., this volume; Langedijk & Fischer, this volume). However, within this line of work, language has been reduced to a set of inputs for individual cognitive processes. This conception of language is at odds with insights from studies of naturally occurring language-in-use. Conversation analysis (CA) and discursive psychology (DP) have shown that, in interaction, individuals treat language as the medium through which social actions are accomplished (te Molder & Potter, Reference te Molder and Potter2005). Moreover, the sequential properties of language-in-use, such as rendering particular responsive actions conditionally relevant or preferred/dispreferred, could be employed as means towards persuasive outcomes (Humă, Reference Humă2023).

This study examines persuasion within a corpus of naturally occurring business-to-business ‘cold’ sales calls. An initial scrutiny of the data led to the identification of two frequently employed formats for designing sales requests: when-formulated requests such as ‘wha- when would be a good time to cal- come down to see yourselves about this.’ and if-formulated requests such as ‘#U::h I >w’s jus’ really seein’< if we could come down and have a chat to you about Yeltel.’ These formats appeared to differ in their effectiveness in eliciting productive responses. Using CA as the method best equipped for the examination of naturally occurring data, the current study aims to identify the mechanisms that underpin the differential outcomes of when-formulated and if-formulated requests. By working out the answer to this question, the current chapter makes both an empirical contribution to the body of knowledge on preference organisation and turn design in persuasion, as well as a theoretical contribution to our understanding of how language-in-use features in persuasive communication.

The rest of the chapter is organised as follows: first, I review the conversation analytic literature on preference organisation within adjacency pairs in order to highlight that and how preference organisational resources could be implicated in persuasion. Then, after presenting the study’s data and method, I present the empirical evidence that illuminates the preference organisational features of when-formulated and if-formulated sales requests that render them more or less effective in eliciting productive responses. The chapter concludes with a discussion of the study’s main findings and implications thereof, as well as a review of possible limitations and directions for future research.

2 Preference Organisation as an Infrastructure for Persuasion

Preference organisation within adjacency pairs represents a set of normative principles that explain the differential relationship between first-pair parts (FPP) and alternative types or formats of second-pair parts (SPP) (Pomerantz & Heritage, Reference Pomerantz, Heritage, Sidnell and Stivers2013). To illustrate this, a first-pair part, such as an offer, ‘prefers’ – that is, invites or promotes – the production of a second-pair part, such as an acceptance, that aligns with the initiating action by carrying out its project, as opposed to a refusal, that frustrates the accomplishment of the course of action initiated by the first-pair part (Schegloff, Reference Schegloff2007). For extensive overviews of preference organisation with adjacency pairs, see Schegloff (Reference Schegloff2007) and Clayman (Reference Clayman, Lawler and Thye2002).

Turns that implement preferred and dispreferred SPPs come in different packages. Specifically, dispreferred SPPs feature one or more of the following design features (Clayman, Reference Clayman, Lawler and Thye2002; Schegloff, Reference Schegloff2007): (1) they are elaborated, usually through accounts, excuses, or disclaimers, (2) they are mitigated, through phrasing that minimises or even omits antagonistic actions, and (3) they are delayed, via inter-turn gaps (but see Kendrick & Torreira, Reference Kendrick and Torreira2015 for further specifications) or via preparatory action such as inbreaths, or delay tokens. These practices for marking dispreferred SPPs mitigate their disaffiliative character (Clayman, Reference Clayman, Lawler and Thye2002; Heritage, Reference Heritage1984b) and can promote the production of aligned responses, for example by providing the space for the FPP speaker to redeploy the initiating action with reversed preference (Schegloff, Reference Schegloff2007).

Not all dispreferred responsive actions are designed with the features of a dispreferred turn format described above. Conversely, preferred responsive actions can sometimes be packaged in a dispreferred format, for example by being delayed or mitigated. The former have been termed ‘flat rejections’ and the latter ‘qualified acceptances’ (Kendrick & Torreira, Reference Kendrick and Torreira2015, p. 273). A delayed and mitigated acceptance can convey possible reluctance (Bilmes, Reference Bilmes2014) or limited commitment to the ongoing course of action (Kendrick & Torreira, Reference Kendrick and Torreira2015). By contrast, delayed but unqualified preferred responses produced in the aftermath of resistance enable respondents to claim having independently changed their position (Stokoe et al., Reference Stokoe, Humă, Sikveland and Kevoe-Feldman2020). Thus, it is not only the type of responsive action, but also its design that should be taken into consideration when studying persuasion-in-interaction. I will come back to this claim in the analysis of the last extract presented in this chapter and in the discussion.

Returning to FPPs, there is compelling evidence that their design is implicated in preference organisation in a way that bears a direct relevance for persuasion. Specifically, initiating actions can be designed to intensify or weaken the preference for an aligned response. Conversation analysts have documented a range of practices and resources for modifying the strength with which an initiating action invites a preferred responsive action. One such resource is epistemic stance. Questions designed to embody a knowing epistemic stance may be better equipped to elicit agreement than questions designed with an agnostic epistemic stance. For example, compared to positively formatted interrogatives, negative interrogatives are usually treated as strongly preferring agreement on the basis of their conduciveness; that is, their presumed embodiment of the speaker’s predisposition for an agreeing response (Clayman & Heritage, Reference Clayman and Heritage2002; Heritage, Reference Heritage2002; Robinson, Reference Robinson2020a). Similarly, prefacing or following a question with a statement in favour of a particular response can exert pressure on the respondent to produce the invited response (Clayman & Heritage, Reference Clayman and Heritage2002).

So far, preference organisation has been discussed with respect to the responsive action invited by the initiating action and the features of the FPP that weigh in on this. Parallel to this action preference dimension, there is also a design preference dimension. Specifically, particular FPPs prefer SPPs delivered in particular formats. The most prominent example is that of yes/no interrogatives that prefer type-conforming responses (i.e., featuring ‘yes’ or ‘no’ tokens) over nonconforming responses (Raymond, Reference Raymond2003). A similar conjecture has been made about wh-questions (Hayashi & Kushida, Reference Hayashi and Kushida2013; Schegloff, Reference Schegloff2007), but empirical studies conducted so far have not yet provided sufficient evidence in support of it (Thompson et al., Reference Thompson, Fox and Couper-Kuhlen2015).

Response design preferences have already been shown to have consequences for individuals’ conduct in commercial encounters. Llewellyn (Reference Llewellyn2015, p. 497) found that asking patrons of a museum to buy a slightly more expensive gift aid ticket using an alternative interrogative such as ‘Would’ya like to gift a:id those today or just pay the standa:rd.’ was less effective than using a yes/no interrogative such as ‘D’you want to add gift aid toda:y?’ While the former provided patrons with the option of choosing to buy the standard ticket, the latter did not offer such a choice and required patrons to first refuse the more expensive ticket. Customers can also take advantage of the constraints on response design mobilised by various initiating actions. Examining requests for service at a copy shop Vinkhuyzen and Szymanski (Reference Vinkhuyzen, Szymanski, Richards and Seedhouse2005, p. 96) noticed that customers’ use of self-oriented declarative requests such as ‘I wanna get uhm some quality copies of this’ allowed shop assistants to swiftly direct customers to the do-it-yourself machines. By contrast, when customers used other-oriented interrogatives ‘can you (.) can you ta:: (.) print up (0.2) on this paper five copies of each of these for me’ shop assistants were constrained by the response options built into the yes/no interrogatives which left them with little room for manoeuvre and required them to produce elaborated dispreferred responses through which to introduce the do-it-yourself option.

Lastly, there is evidence to suggest that some initiating actions can mobilise combined action and turn design preferences. Specifically, remote requests have been documented to prefer acceptances embodied by a response token accompanied by a display of commitment (Lindström, Reference Lindström, Raymond, Lerner and Heritage2017). More recently, a study into the preference organisation of unpolarised positively formatted polar interrogatives used to implement simple questioning found that they prefer unconditionally formatted affirmative and disaffirmative responses over conditional responses (Robinson, Reference Robinson2020b). These studies suggest that both action and design dimensions of a responsive turn are implicated in the production of preferred and dispreferred SPPs.

Having reviewed extant conversation analytic research on preference organisation within adjacency pairs, this section has highlighted how FPPs (1) can be designed to intensify the pressure for a preferred SPP and how (2) through the design of the FPP and its preference for a particular response format respondents can be provided with more or less space to extricate themselves from the constraints of producing an aligning response. Thus, it has become hopefully apparent that and how preference organisation can lend itself as one of the interactional structures that underpin persuasion. As a conversational activity, persuasion is successful if the persuaders’ FPPs manage to elicit preferred SPPs from the persuadees. As such, persuaders need to design their requests, offers, or invitations in ways that more readily encourage their acceptance and/or restrict their rejection (cf. Sorlin, this volume). These insights will be applied to the analysis of when-formulated and if-formulated sales requests, after the study’s data and method have been introduced in the next section.

3 Data and Method

The corpus examined in this study comprises 159 business-to-business ‘cold’ (unsolicited) calls recorded between 2014 and 2016 in four British companies. Ethical approval for collecting and analysing these recordings was given by Loughborough University’s Ethics Approval (Human Participants) Sub-Committee.

All calls were initiated by salespeople who were contacting prospective customers (‘prospects’ in sales parlance) on behalf of companies selling multifunctional printers, telecommunication systems, or advertising services. As ‘cold’ calls, these conversations were mainly geared towards gathering information about the prospects’ companies and setting up appointments for subsequent sales visits (Humă, Reference Humă2018; Humă & Stokoe, Reference Humă, Stokoe and Sikveland2020). Even though the calls were treated by all parties as sales-oriented, the eventual sale would typically occur after several rounds of discussions and negotiations.

To assemble the collection (Hoey & Kendrick, Reference Hoey, Kendrick, de Groot and Hagoort2018), I first scrutinised the corpus (by listening to the audio recordings while reading the transcripts thereof) for all instances of sales-related if-formulated and when-formulated requests. By that, I mean requests implementing courses of action that were implicated in the progress of the conversation towards an eventual sale. The two request configurations were chosen because of their comparability and because of the relative high frequency with which they appeared in the corpus, compared to other configurations.

Fifty-four candidate cases were identified: seven when-formulated and 47 if-formulated requests. An eligibility check led to the removal of 12 if-formulated requests that initiated presequences (e.g., ‘↑I was w↑onderin’ if you could help me.’) because an equivalent when-format was not available for this action in this slot. The final collection, comprising 42 cases, consists of the following five actions, each exemplified below by either an if-formulated or a when-formulated request:

• Information requests: ‘Do you happen to know when these are due to expire and when you’re .h uhm >next reviewing<¿’

• Meeting requests (whereby the salesperson asks the prospect for a meeting): ‘#U::h I >w’s jus’ really seein’< if we could come down and have a chat to you about Yeltel.’

• Scheduling requests (whereby the salesperson asks for or proposes a particular timeframe for the meeting): ‘U:h just (a) wonderin’ if u::h you’re available sometime (.) °December or January time°?’

• Future contact requests (whereby the salesperson asks for or proposes a non-specific future contact opportunity such as a call, an email exchange, or a meeting): ‘So when do you want me to recontact you Tom.’

• Switchboard requests: ‘Wonder if I could .hhh ↑just have a brief m- u:hm moment of the: (.) the business manager’s time there?’

The data were transcribed using the Jefferson (Reference Jefferson and Lerner2004) system developed for conversation analysis in order to capture the minutiae of speech production such as silences, overlaps, intonation, or laughter as features that participants treat as meaningful resources for building social actions. The data were analysed using conversation analysis, with a focus on preference organisation, turn design, and action formation (Schegloff, Reference Schegloff2007). The analytic process consisted of multiple rounds in which each case was scrutinised individually and then emergent observations were compared across the entire collection. The cases selected to be included in this chapter represent the clearest and most concise examples of the identified patterns.

4 Analysis

This section will show that, compared to if-formulated sales requests, when-formulated sales requests appear to be more effective in eliciting a productive response (Stokoe et al., Reference Stokoe, Humă, Sikveland and Kevoe-Feldman2020). Productive responses not only align with the initiating action, but also move the conversation forward towards a successful completion of the overarching activity (Robinson, Reference Robinson, Sidnell and Stivers2013) that the interlocutors are engaged in, for example setting up a sales meeting or extracting useful information about the prospect’s company (see Humă & Stokoe, Reference Humă, Stokoe and Sikveland2020, for an overview of the different activities comprised in cold calls). I start by examining when-formulated requests.

5 Discussion

Drawing on a large corpus of naturally occurring business-to-business ‘cold’ calls, this study investigated the comparative effectiveness of when-formulated and if-formulated sales requests in eliciting responses that advance the commercial activity. The reviewed empirical evidence suggests that the former are more effective than the latter in mobilising a productive response that not only aligns with the ongoing course of action, but that also enables the overarching activity to progress, for example by moving from an agreement to meet to a scheduling of the meeting. The basis for the differential outcomes of these request configurations seems to lie in how they leverage preference organisational principles to restrict the opportunities for producing dispreferred responsive actions.

Across the collection, when-formulated sales requests appear to set up several constraints upon the responsive action. As FPPs of request sequences, they promote acceptance as the preferred responsive action. The preference for prospects to accept what the salesperson is asking for is further intensified through the design of the request. Specifically, most when-formulated sales requests do not index any contingencies that could preclude their fulfilment. Instead, they embed the presumption that the requestable can and should be provided. Furthermore, when-formulated sales requests also restrict the possibilities for formatting the SPP by projecting aligned responses that feature a time reference. Thus, producing a rejection of the request requires prospects to break with both the action preference of the FPP and with the projected design of their responsive action. Taken together, these characteristics provide prospects with little room to manoeuvre out of the constraints set up by the request. Simply refusing to comply is not an option for them.

By contrast, if-formulated sales requests put both acceptance and refusal on the table. While, as requests, the action preference of these FPPs promotes the former response, still their design does not reinforce it. If-formulated sales requests index the salesperson’s low entitlement to have the request granted as well as possible contingencies that may hinder the prospect in complying with it. Importantly, the yes/no interrogative format of these requests invite type-conforming ‘yes’/’no’ responses (Raymond, Reference Raymond2003). As a result, they provide more flexibility to prospects refusing the request. Thus, saying ‘no’ is an entirely possible, albeit still accountable response (see Extract 3.4). Interestingly, not all aligned responses to if-formulated requests are also productive ones. It appears that responses which lack a display of commitment or investment on the part of the prospect hamper the progressivity of the sale and can jeopardise the success of the call (Lindström, Reference Lindström, Raymond, Lerner and Heritage2017).

The current study directly builds on prior research by Llewellyn (Reference Llewellyn2015) and Vinkhuyzen and Szymanski (Reference Vinkhuyzen, Szymanski, Richards and Seedhouse2005) on the interactional consequences of different request formats in commercial encounters. It extends this line of work by comparatively examining two new request configurations and their use as vehicles for five different actions: information requests, meeting requests, scheduling requests, future contact requests, and switchboard requests. Thus, the comparative advantage of when-formulated requests over if-formulated requests is evidenced across a range of actions, which increases the robustness of the pattern.

The study contributes to a growing body of work that examines persuasion in naturally occurring service and sales encounters using conversation analysis and discursive psychology (Humă et al., Reference Humă, Stokoe and Sikveland2019, Reference Humă and Stokoe2020; Llewellyn, Reference Llewellyn2015; Mazeland, Reference Mazeland2004; Niemi et al., Reference Niemi, Pullins, Kaski, Lindström, Laury, Peräkylä and Sorjonen2021; Pinch & Clark, Reference Pinch and Clark1986; Sikveland & Stokoe, Reference Sikveland and Stokoe2016). It shows how the infrastructure of preference organisation underpins persuasive conduct in interaction. Specifically, it illuminates how persuasion can be accomplished by designing sales requests that restrict interlocutors’ range of responsive opportunities to promote aligning responses more strongly. While similar observations have already been put forward – for example Bone (Reference Bone2006) notes that salespeople in the home improvement sector avoid yes/no questions like ‘are you interested in a free quotation’ in favour of questions like ‘are windows/kitchen a priority when in the future you are going to refurbish your house’ – this chapter is the first to provide an empirically grounded explanation for why the latter formulation may be more persuasive.

The strength of the approach taken here lies in investigating language-in-use holistically as it is employed spontaneously in real-life persuasive interactions (see also Humă, Reference Humă2023). Thus, it minimises both the researcher’s intervention into and preconceptions about the linguistic realisation of persuasion. Linguistic features are examined in the sequential and interactional environments in which they are employed and are analysed on the basis of participants’ orientations to them. These methodological principles are crucial for providing an accurate and empirically grounded view of persuasion-in-interaction. To give just one example, a decontextualised treatment of ostensibly aligned responses to if-formulated requests such as ‘Uy:eah=you could do:’ (Extract 3.6) might have missed noting that in fact this is an unproductive response. As such, detailed, context-sensitive analyses of persuasion-in-interaction can produce insights that standardising and quantifying approaches (i.e., coding and counting cases) might obscure.

This study is not without limitations. First, all cases originate from one specialised institutional setting – business-to-business ‘cold’ calls – in which caller and call taker align as salesperson and prospective customer in the accomplishment of various sales-oriented activities. While a wider range of actions are considered than other similar studies have done in the past, still, the applicability of the findings to other institutional settings should be further investigated (Fuchs, this volume). Second, it is worth noting that the collection on which this study is based encompasses a larger proportion of if-formulated than when-formulated requests. This uneven distribution and the natural configuration of the cases prevent direct comparisons across request formats, actions, and their sequential environment. Given that there is compelling CA research documenting the importance of the sequential and interactional environment in the selection of request formats (Curl & Drew, Reference Curl and Drew2008; Fox & Heinemann, Reference Fox and Heinemann2017) subsequent research could further attempt to illuminate the consequence for persuasion of the co-constitutive nature of request formulations and the environment in which they are deployed. Finally, it must also be acknowledged that the analysis presented in this chapter focused solely on proximal interactional consequences of if-formulated and when-formulated requests. An exploration of the ultimate outcome of the calls was beyond the scope of the study and was considered uninformative for the research question under investigation.

To conclude, this study is one of the few that examines language and persuasion in a ‘natural laboratory’ environment and thus has been able to uncover the crucial role that sequential properties of language-in-use have in persuasion. As such, it calls into question the hitherto exclusive conceptualisation of persuasion as the result of social-cognitive information processing mechanisms. Without doubt, more research is needed that uses naturally occurring data in order to expand our understanding of the interactional mechanisms that underpin persuasion.

1 Introduction

Election campaigns have been subject to considerable scientific scrutiny over time, with scholars exploring the persuasive effects of campaign discourse on different voter communities (cf. Lanning, Reference Lanning2005; Mayhew, Reference Mayhew2008). Similarly, linguists have examined how Aristotle’s three ‘aspects involved in rhetorical persuasion’ (Claridge, Reference Claridge2010, p. 217) can be exploited to sway electorates (cf. Partington & Taylor, Reference Partington and Taylor2017; Reyes, Reference Reyes2011; Sorlin, this volume).

Investigations into the use of stance expressions in campaign discourse are a case in point and have been gaining momentum in recent years (Breeze, Reference Breeze2018, Reference Breeze2020; Cabrejas-Peñuelas & Díez-Prados, 2014). This study seeks to enhance this line of research in three ways: first, it will show how a method previously applied in corpus linguistics (i.e., key semantic domain analysis; Rayson, Reference Rayson2008) can be fruitfully combined with Martin and White’s (Reference Martin and White2005) Appraisal Theory to classify features of evaluation in larger text corpora.Footnote ¹ Second, the study will provide systematic insights into the ways negative evaluations are strategically deployed in online election campaigns. Finally, the study reveals how specific (types of) negative evaluations can change during a main phase of the US presidential elections.Footnote ²

More precisely, the study tracks negative evaluations in the online Twitter profile of Donald J. Trump and Joe Biden from the start of the respective online election campaigns to Election Day. To reveal how two different political parties in the US (Democrats and Republicans) shape the direction and the persuasive appeal of their respective election Twitter campaigns, a self-compiled corpus of 5,888 tweets (and retweets), totalling 105,773 words (tokens) and containing 1,667 negative evaluations was compiled. The corpus was analysed systematically, employing a mixed-method approach including the semi-automatic detection of attitudinal lexis as well as a later manual classification (and interpretation) of types, targets and objects of evaluation in their contexts of use.

2 Attitudinal Evaluation in Political Discourse

This study examines the negative evaluations of political candidates in the US presidential elections in 2020 and the persuasive effects such evaluations are likely to have on US voters. A primary upshot of a systematic analysis of (types of) negative evaluations is that it can expose the cultural (and ideological) beliefs and values to which politicians ascribe and that they wish to evoke in their audience. Kreis (Reference Kreis2017, p. 613), for instance, shows that politicians deploy ‘negative other-presentations’ of political opponents that often coincide with ‘positive self-presentations’. This campaign tactic, that Kreis (Reference Kreis2017, p. 614) calls ‘evaluative scapegoating’, helps politicians construct and negotiate their own public image in political campaigns, especially on social media. To illustrate, evaluations in the tweets of former US president Donald J. Trump have been shown to be based on ideological concepts firmly linked to the ‘alt-right’ movement (Lorenzo-Dus & Nouri, Reference Lorenzo-Dus and Nouri2021, p. 413). Such views include revisionist and polarised descriptions of a nefarious liberal elite that aims to undermine the rights of ‘ordinary’ US citizens – the latter being a fictional group of its own kind (Hoffmann, Reference Hoffmann2018, p. 76). Studying evaluations can be a useful practice to uncover how such beliefs are discursively constructed, reproduced, or indeed, how they make their way into mainstream political communication to begin with.

The study takes Martin and White’s appraisal theory as one of its conceptual cornerstones since the framework helps to capture and classify types of negative evaluations in political tweets.Footnote ³ It is based on the identification of three categorical domains of evaluation (also called systems), i.e., attitude, graduation and engagement. While the latter two systems are devoted to ‘engage with, source and amplify […] various evaluations and ‘positions’ within a text’ (Ross & Caldwell, Reference Ross and Caldwell2020, p. 16), the system of attitude captures the linguistic resources used to ‘express emotions, evaluations, and valuations’. Attitude can arguably be considered as a description of the semantic core of any given act of evaluation, while the other two systems boost, mitigate or enrich its semantic (and pragmatic) effects. Within the system of attitude, three subsystems can be distinguished, namely affect, appreciation and judgment (see Table 4.1).

Affect-based resources are often employed to induce emotional responses in recipients, but they may also reflect speakers’ affective stance toward a given state of affairs (see Example 1). In contrast, judgment evaluations refer to moral qualifications of human beings (see Example 2), that are typically realised in a range of subsystems related to different degrees of personal capacity, normality, tenacity, propriety or veracityFootnote ⁴. Such value judgments are clearly based on speakers’ individual or social beliefs, norms or expectations.

The third subsystem of appreciation (see Example 3) ‘gives expression to the speaker’s aesthetic views [on non-sentient objects or entities] rather than their emotions or feelings’ (Hoffmann, Reference Hoffmann2018, p. 61).

The study classifies patterns of attitudinal evaluation since ad hominem evaluations are particularly suited to provide insights into the underlying socio-political ideologies of politicians. Attitudinal evaluations can take the form of inscribed or invoked evaluations (Martin & White, Reference Martin and White2005, p. 67). Inscribed evaluations are ‘explicitly presented by means of a lexical item carrying the [negative or positive] value’ (White, Reference White1998, p. 53). In contrast, invoked evaluations cannot be tied to the evaluative load of a single expression. Instead, they need to be lifted implicitly from linguistic contexts in which they are embedded. Then, a context-sensitive meaning may suggest itself and ultimately override the (negative or positive) polarity of the single expression under study. The key domain method used in this study primarily targets inscribed evaluations. Invoked evaluations are not explored in any systematic way which is likely to impact the findings of this study.

Attitudinal evaluations can also take different formal shapes. Formal realisation patterns can range from single expressions, collocations, strings of words to single or multiple adjacent utterances (Hoffmann, Reference Hoffmann2018, p. 62). Since the study focuses on inscribed evaluations exclusively, the investigation delimits the scope of its quantitative analysis to the word classes of nouns, verbs, adjectives and adverbs. This implies that larger syntagms, such as complex phrases or clauses, are not considered as basic units of analysis. The quantitative findings reported in Section 6 will thus be based on this fundamental practice. For the (qualitative) discussion of negative evaluation some more implicit (or invoked) types of negative evaluation will be presented.

The scope of the study is constrained since it takes a closer (quantitative and qualitative) look at negative evaluations but excludes positive evaluations. This decision seems justified on three grounds: first, recent election campaigns have been shaped by what Ross and Caldwell (Reference Ross and Caldwell2020, p. 14) have called a trend of ‘going negative’ in political campaigning, stressing the relevance of negative evaluations for the overall campaign strategy. Second, a quantitative investigation of negative evaluations in this study allows for a systematic comparison to earlier studies focusing on negative evaluations in political discourse (Cabrejas-Peñuelas & Díez-Prados, 2014; Hoffmann, Reference Hoffmann2018). Third, the analysis of negative evaluations already provides a rich collection of findings that must be contextualised and discussed within the scope of this chapter. This notwithstanding, future research on politician’s systematic use of positive evaluations is encouraged since it promises to yield insights that could potentially refute or reinforce the arguments made in this study.

3 Previous Research

Despite a growing body of work on political rhetoric and political discourse analysis, studies that adopt the framework of appraisal theory (Martin & White, Reference Martin and White2005) to explore the evaluative load of political discourse are rather scarce and piecemeal (cf. Angouri & Wodak, Reference Angouri and Wodak2014). Some studies have explored how attitudinal lexis is used in political debates (Cabrejas-Peñuelas & Díez-Prados, 2014), in online campaign tweets (Hoffmann, Reference Hoffmann2018) or the newspaper coverage of mid-term elections (Mayo & Taboada, Reference Mayo and Taboada2017). While the latter uncover the ideological positions adopted by newspaper editors, authors and readers, Cabrejas-Peñuelas and Diez-Prados (Reference Cabrejas-Peñuelas and Diez-Prados2014) track how politicians’ evaluations change strategically as the televised electoral debate moves from one topical section to the next. Hoffmann (Reference Hoffmann2018) shows how the strategic use of negative evaluations over time can spread far-right ideology, based on a recurring set of objects and targets of evaluation. Similarly, Ross and Caldwell show how Trump strategically ‘goes negative’, employing a set of negative evaluations to ‘attack and undermine the character of his political opponent’ (2020, p. 13).

Note that most of these studies focus on attitudinal (judgment) evaluations. Other scholars have explored the use of emotional lexis in political discourse (cf. Wahl-Jorgensen, Reference Wahl-Jorgensen2019). For instance, Breeze (Reference Breeze2018) adopts a corpus-assisted approach to discourse analysis to study how expressions of emotion are used differently in a corpus of press releases by the British far-right UKIP compared to the centre-left Labour party. Breeze shows that the two parties ‘offer different repertoires of affective-discursive practices’ (2018, p. 39). In addition, the study revealed that the UKIP party tends to use more affective expressions in their press releases than Labour; and these affective devices commonly instigate feelings of fear and anger in readers. In contrast, the affective lexis in Labour press releases seemed to privilege emotions of ‘worry’ or ‘concern’ (Breeze, Reference Breeze2018, p. 35f.). In a more recent paper, Breeze (Reference Breeze2020) investigates the use of affective expressions in tweets of the British UKIP politician, Nigel Farage. We find that Farage’s recurring use of emotional expressions is not accidental but designed to ‘bring anger into the public sphere’ (Breeze, Reference Breeze2020, p. 18). These studies provide evidence for the fact that political communication rests on socio-political ideologies that are repeatedly evoked to reach a target votership and persuade readers (or viewers). In addition, they show that, based on the systematic and recurring use of persuasive devices, evaluations and emotions are likely to be employed in a strategic and deliberate manner rather than being incidental.

There is a large body of work on the persuasive use of rhetorical strategies in political discourse. It ranges from studies that explore the persuasive dimension of speech acts (House & Kádár, Reference House and Kádár2021; Stopfner, Reference Stopfner2021), patterns of interaction (Ekström, Reference Ekström2001; Lauerbach, Reference Lauerbach, Cap and Okulska2013; Loeb, Reference Loeb2017; Montgomery, Reference Montgomery, Ekström and Patrona2011), pragmatic inferences (Fetzer & Bull, Reference Fetzer and Bull2012), discourse markers (Fetzer, Reference Fetzer2014) and transitivity patterns (Hart, Reference Hart2013; Zhang, Reference Zhang2017), to the representation of social actors (Lundell, Reference Lundell2010; Page, Reference Page2003), the strategic use of personal pronouns (Bello, Reference Bello2013; Coesemans & de Cock, Reference Coesemans and De Cock2017) and conceptual metaphors (Charteris-Black, Reference Charteris-Black2018, Reference Charteris-Black2019; Lakoff, Reference Lakoff2010; Lakoff & Wehling, Reference Lakoff and Wehling2016). While these features can all trigger decisive persuasive effects in political discourse, their analysis is not part and parcel of this chapter, I will thus forego an extensive discussion of their individual research goals and findings in this section. Instead, I shall now take a closer look at some linguistic work that has explored the linguistic (and persuasive) styles of US American presidents, including features of evaluation and emotion (cf. Schoor, Reference Schoor2017, p. 660). Proctor and Su, for instance, examine how US presidential candidates strategically employ personal pronouns to ‘evoke nationalistic views when delivering their speeches’ (Reference Proctor and Su2011, p. 3251). Capone (Reference Capone2010) analyses how former US president Barack Obama makes strategic use of personifications, short personal stories and aspects of polyphony to convince his audience. Oddo (Reference Oddo2011, p. 287) uncovers how US presidents Roosevelt and (George W.) Bush draw on ‘polarizing lexical resources that constitute “Us” and “Them” as superordinate thematic categories that covertly legitimate war’. Sowińska (Reference Sowińska2013, p. 792) conducts a critical analysis of ‘metaphors, assertion-based patterns and thesis-antithesis’, revealing the ideological basis of US president George W. Bush’s concept of freedom. In a similar vein, Bhatia’s (Reference Bhatia2006) thematic analysis of political press conferences contrasts how the Chinese President Jiang Zemin and the former US president George W. Bush address controversial topics quite differently, stressing (or de-emphasising) aspects of positivity, mutual interest or power relations. This work notably shifts the focus of analysis from an intracultural to the important intercultural domain of political discourse analysis. The study thus reflects the subtle discursive modifications that are required by (and in) intercultural acts of diplomacy.

More recently, scholars have focused on the rhetorical style of former US president Donald J. Trump (cf. Schneider & Eitelmann, Reference Schneider and Eitelmann2020), initially finding his style of oratory to exhibit high degrees of spontaneity and simplicity, ‘never leav[ing] the realm of the casual’ (McWhorter, Reference McWhorter2017).Footnote ⁵ More recently, however, Clarke and Grieve (Reference Clarke and Grieve2019; see also Egbert & Biber, Reference Egbert, Biber, Schneider and Eitelmann2020) showed that Trump’s expressivity is indeed much more versatile. In fact, Trump makes use of four different writing styles on Twitter, and they are used in different degrees of frequency and dominance before, during and after the 2016 US presidential election phase (cf. Egbert & Biber, Reference Egbert, Biber, Schneider and Eitelmann2020). For instance, features of what the authors call campaigning style was arguably used more frequently in the run-up phase to the 2016 US presidential elections. It includes frequent mentions of first-person pronouns in both subject and object position, modals of predication, time adverbials, possessive determiners and a heavy use of hashtags and capitalisations (Clarke & Grieve, Reference Clarke and Grieve2019, p. 15). In contrast, other expressive styles, such as the engaged style lost prominence during the election phase but turned out to be more dominant in pre-and post-election times.Footnote ⁶

Such expressive diversity notwithstanding, there appears to be a consensus among discourse scholars that Trump’s styles are typically characterised by a frequent use of evaluative resources, particularly expressed by attributive and predicative adjectives (Egbert & Biber, Reference Egbert, Biber, Schneider and Eitelmann2020, p. 30f.) or a heavy use of intensifers (cf. Stange, 2020). Ronan (Reference Ronan2021, p. 81), for instance, finds that in Trump’s typical Twitter style ‘features of evaluative language are strongly represented’. However, in most of these studies, such remarks on evaluation are made in passing and different types and dispersions of evaluative features are not measured and analysed in more detail. This makes investigations targeting the systematic patterns of evaluations in political discourse even more relevant. To this end, this study hopes to shed some light on this important facet of persuasive communication in political online discourse.

4 The Key (Semantic) Domain Method

The key (semantic) domain method (KDM) is used in this study to capture evaluative lexis in larger collections of text. It has already been widely adopted in corpus stylistics (Culpeper, Reference Culpeper2009; McIntyre & Walker, Reference McIntyre, Walker, O’Keeffe and McCarthy2010) and in the corpus-assisted discourse analysis of (conceptual) metaphors (Potts & Semino, Reference Potts and Semino2019; Semino et al., Reference Semino, Hardie, Koller and Rayson2005). More recently, evaluation research has discovered the method and employed it for its own aims and purposes but not in political text types (Hidalgo-Downing & Hanawi, Reference Hidalgo-Downing, Hanawi, Aijmer and Lewis2017).

The tool used to engage in KDM for the present purposes is Wmatrix. Texts can be uploaded to the tool and are automatically POS tagged (CLAWS tagger; Rayson & Garside, Reference Rayson and Garside1998). In a second stage, Wmatrix then links each expression in a text (automatically) to ‘general fields of meaning using a taxonomy derived from the labels in the Longman Lexicon (McArthur, Reference McArthur1981)’ (Semino et al., Reference Semino, Hardie, Koller and Rayson2005, n.p.). The result is an outline showcasing the frequency of semantic domains present in the corpus, thereby reflecting their relative dominance. The overview thus mirrors the topical landscape of the corpus in question. The linguistic expressions (and their linguistic co-texts) can be accessed in relation to the semantic domains to which they are subsumed. To determine the semantic prevalence of semantic domains, each target corpus needs to be compared to a reference corpus, compatible in size and design. In this study, the two subcorpora (Biden subcorpus vs Trump subcorpus) serve as reference corpora for each other, yielding a string of positively keyed semantic domains in a corpus (relative overuse) and negatively keyed semantic domains (relative underuse). It turns out that some key semantic domains are more likely to reveal attitudinal lexis than others (see Table 4.2). This study thus selected a set of attitudinal domains exclusively and analysed the lexical expressions (and their linguistic co-texts) which were subsumed to these categories. More specifically, nouns, verbs, adjectives and adverbs which proved to have a negative polarity were selected and manually classified in different types of attitudinal evaluation, using Martin and White’s attitudinal framework, described in Section 2. In the end, the results of this analysis open a window into the use of attitudinal evaluation in each subcorpus (see Table 4.2).Footnote ⁷

5 Corpus Design

The Election Twitter Corpus (ETC) compiled for this study is partly sourced from the Trump Twitter Archive (http://www.thetrumparchive.com/) and partly built by means of manual tweet extraction from Joe Biden’s Twitter account (@JoeBiden) from 1 July to 23 October 2020. The corpus comprises 5,888 tweets (and retweets), including 105,773 words (tokens). Note that the corpus size is larger than the corpus of an earlier study that also focused on the use of negative evaluations in the 2016 US presidential election Twitter campaign between Donald Trump and Hillary Clinton (Hoffmann, Reference Hoffmann2018). This difference can be explained by the fact that the corpus in this study includes author retweets in its analysis while my earlier study did not. Retweets (by the two presidential candidates themselves) were deliberately retained in this study for two reasons:

1. (a) Author retweets are used quite pervasively by Donald Trump (see Figure 4.1), while Biden uses them much more rarely. At least for Trump’s Twitter activity, they contribute considerably to the overall evaluative prosody linked to his Twitter handle and should thus be considered.

2. (b) Author retweets frequently contain negative evaluations (either as part of the quoted message or as part of a meta-comment that the candidates attach to individual retweets). Note that the inclusion of author retweets affects total word counts and relative frequencies of evaluative lexis in the subcorpora. In addition, formally identical retweets are discarded.

Figure 4.1 Number of tweets (dark grey) and retweets (light grey) for @realDonaldTrump in October 2020; source: www.tweetstats.com.

(accessed: 21 May 2022)

Four different subcorpora (for each presidential candidate) comprise all tweets and retweets published on the official Twitter accounts of both candidates in the months leading up to the presidential election in late October 2020.Footnote ⁸ The time period for the extraction of tweets is limited to 01 July to 23 October 2020, capturing the key phase of the presidential race from the official nomination of candidates to Election Day. Tweets before or after this period are not considered.

During this time period, @JoeBiden tweeted 42,732 words in 1,383 tweets, while the corpus of @realDonaldTrump in the same time frame comprises 63,041 (word) tokens in 4,505 tweets (see also Figures 4.2 and 4.3).

Figure 4.2 Number of tweets/month for @JoeBiden and @realDonaldTrump during the US presidential election campaign 2020; source: www.tweetsstats.com.

(accessed: 21 May 2022)

Figure 4.3 Average tweets/day for @JoeBiden and @realDonaldTrump during the US presidential election Campaign 2020; source: www.tweetsstats.com.

(accessed: 21 May 2022)

All tweets are analysed using the Wmatrix software (https://ucrel.lancs.ac.uk/wmatrix/, version four). It provides a suitable online interface for the key semantic domain method (Rayson et al., Reference Rayson, Archer, Piao and McEnery2004), as explained in Section 4. In line with previous studies, ‘the different types of evaluative devices [detected are] weighed against the total amount of evaluation in the text’ (Hoffmann, Reference Hoffmann2018, p. 66; cf. Cabrejas-Peñuelas & Díez-Prados, Reference Cabrejas-Peñuelas and Diez-Prados2014, p. 168). Quantitative results are presented in percentages, relative frequencies are listed when statistically relevant to the findings.

While epithets or nicknames are precluded from the quantitative analysis due to their high frequency in the dataset, they are relevant at a later stage of the chapter, in the ensuing qualitative analysis (see Section 8). The respective section explores how both presidential candidates describe each other, using specific patterns of negative evaluations. Duplicates or formatting errors are deleted or corrected. Statistical significance is determined only in cases in which quantitative findings proved to be relatively close (p-values, log-likelihood) between variables (specific attitudinal categories) of the Trump and the Biden subcorpora.

6 Attitudinal Evaluations in the ETC

The quantitative analysis of negative evaluations in the ETC yields a sum total of 1,667 negative evaluations. This is a slight increase to the 1,383 negative evaluations that were used by the two candidates of the 2016 US presidential election in their campaigns on Twitter (cf. Hoffmann, Reference Hoffmann2018, p. 66). Of these 1,667 negative evaluations, roughly twice as many are published from Donald Trump’s (n=1,141) account than from Joe Biden’s (n=526).Footnote ⁹ To this end, the frequent number of negative evaluations, detected in the Trump subcorpus, corroborates what previous studies have found to be the case, namely a ‘strong negative emotional loading’ of Trump’s language use (Ross & Rivers, Reference Ross and Rivers2020, p. 9).

Figure 4.4 shows the dispersion of attitudinal evaluations across the ETC. What stands out is the high frequency of judgment evaluations. Almost three-quarters of all attitudinal evaluations can be assigned to this category (cf. Cabrejas-Peñuelas, Reference Cabrejas-Peñuelas2020; Cabrejas-Peñuelas & Diez-Prados, Reference Cabrejas-Peñuelas and Diez-Prados2014; Hoffmann, Reference Hoffmann2018). The second most frequent attitudinal subsystem is appreciation, followed by affect. More substantial insights are revealed in Figure 4.5 that shows different types of attitudinal evaluations.

Figure 4.4 Percentage of attitudinal subcategories in the ETC.

Figure 4.5 Percentage and RF/10,000 of attitudinal subcategories for negative evaluations in @JoeBiden and @realDonaldTrump in the ETC.

As can be seen, judgment evaluations rank highest in both evaluation profiles (62.3% of all evaluations for Biden and 58.3% of all evaluations for Trump). While these percentages seem to suggest that Biden uses judgment evaluations more frequently than Trump, a closer look at the respective relative frequencies (rf per 10,000 words) shows that Trump effectively deploys judgment evaluations more often than Biden (Biden: rf/judgment: 76.8 vs Trump: rf/judgment: 108.8). As will be illustrated, one of the main reasons for the elevated number is Trump’s more flexible choice of different subtypes of judgment evaluations in his tweets (see Section 7).

Likewise, Trump deploys more appreciation evaluations than Biden. In fact the relative frequencies of appreciation evaluations (Trump: rf/appreciation: 57.6 vs Biden: rf/appreciation: 29.1) reveal that Trump uses them almost twice as often as Biden. With a view to topical choices, Biden’s use of appreciation largely revolves around the impact of the coronavirus pandemic on the health of US citizens. He describes the virus as ‘grim’, ‘deadly’, ‘bad’ or ‘devastating’ (Example 4). He likewise discusses the social and natural effects of global climate change as ‘unrelenting’ or ‘horrifying’ (see Example 5). There is also criticism of racial discrimination, challenging Trump’s efforts to criminalise protestors who rallied to address the use of systematic violence in the police force, such as ‘unwarranted police violence’, ‘divided nation’, ‘racial justice’.

On several occasions, Donald Trump also tweets about the global pandemic and its negative impact on US society, but he does so much less frequently and in a different fashion: while Biden primarily focuses on the personal hardships of infected patients, Trump frequently uses COVID to launch verbal attacks on the Chinese state or its government, holding it responsible for the outbreak of the pandemic (‘the Chinese virus’).

Trump’s appreciation evaluations dominantly target objects or events linked to what Trump calls the ‘liberal democratic left’ (see also Section 7). For example, he criticises the ‘feckless Democratic leadership’ or ‘the radical left movement’. More generically, he warns of ‘dangerous cities’, ‘unsolicited ballots’ or ‘socialist healthcare schemes’. Such entities are often used metonymically to stand for larger social groups or collectives, such as buildings for parties or movements for protestors. So, one could equally class them as implicit judgment evaluations. Note that this type of demeaning tweet tends to surface more often in Trump’s retweets than in his tweets. It is probable that this trend suggests that retweets allow the candidate to deflect authorial responsibility for the original tweet to a third party while they support the authors of these tweets and authorize their ideological position through the act of quoting (see Example 6).

Trump’s negative affect evaluations primarily centre on negative surprisal markers (Example 7). Examples below show tweet-initial interjections (‘Wow!’, ‘Oh’), followed by a statement with negative prosody. Such constructions frequently describe the political opponent (their actions or behaviour) in the dataset. As can be seen, the resulting negative prosody of the linguistic context typically overrides a potential positive reading of the initial interjection:

In addition, the same negative affect evaluations are frequently located at the end of tweets, where they can function as global stance markers, expanding the negative qualification linked to the entire utterance. Again, the negative affect, in this position, expresses Trump’s discontent with the actions of his political opposition (see Example 8). By contrast, tweet-initial affect markers typically reflect emotions of anger or sadness, expressing Trump’s emotional response to victims of natural disasters or crimes (Example 9). In the latter case, the lexical stance markers form integral parts of the elliptical clauses in that they are embedded.

Let us now shift our attention from appreciation to judgment evaluations. More precisely, the different subsystems of the judgment category will be examined more closely, explaining how each of the categories is used in the Democratic and Republican Twitter profiles under study.

7 Judgment Evaluations in the ETC

Figure 4.6 shows the dispersion of judgment evaluations in the Biden subcorpus of the ETC. As can be seen, capacity and propriety evaluations appear in much larger numbers than all of the other judgment subsystems.

Figure 4.6 Temporal dispersion of negative judgment evaluations on @JoeBiden during the US presidential election campaign 2020.

Hoffmann (Reference Hoffmann2018, p. 71) revealed similar results in his study on negative evaluations in the 2016 US presidential election campaign. He showed that Hillary Clinton, the Democratic candidate for the US presidential elections in 2016, equally made dominant use of capacity and propriety evaluations in her Twitter campaign (see Figure 4.7). Note that the remaining judgment categories, namely, veracity, tenacity and normality, are used much more rarely by the Democratic candidates.

Figure 4.7 Temporal dispersion of negative judgment evaluations on @HillaryClinton during the US presidential election campaign 2016.

In addition, we can observe that at the beginning of Biden’s election campaign capacity evaluations dominate, while propriety evaluations increase at the end of the election phase. The number of capacity evaluations drops in September 2020, while the frequency of propriety evaluations simultaneously increases. The steady rise of propriety evaluations can be possibly explained by the event of two televised election debates that were broadcast on national television in late September and early October 2022. Both debates arguably represent ‘focal points in the electoral process’ (Jennings et al., Reference Jennings, Bramlett, McKinney and Hardy2020, p. 2). The rise of propriety-based negative evaluations in the run-up to both debates might thus indicate that both contenders increasingly try to debase the (moral) character of the political opponent (Jennings et al., Reference Jennings, Bramlett, McKinney and Hardy2020, p. 4).

A closer look at capacity evaluations in July and August 2020 in their respective contexts of use suggests that Biden frequently targets Trump’s leadership abilities. More precisely, frequent negative capacity evaluations challenge official government policies for which Trump as US President is held accountable. This includes Trump’s allegedly ‘poor’ track record of creating jobs, his dismantling of the US health care system or his ‘inefficient’ fight against the COVID pandemic (see Examples 10 or 11).

The frequency of capacity evaluations by Biden’s 2020 Twitter election campaign is notably higher than the number of capacity evaluations on Hillary Clinton’s Twitter account in the 2016 US presidential election campaign. At the time, Hillary Clinton entered the election campaign as the running candidate for the governing party, in other words, the Democrats. So, she found herself in a position to defend rather than challenge government policies. The high frequency of propriety evaluations, relative to a much lower number of capacity evaluations, reflects this fact. Note that Clinton’s election team appeared to focus her Twitter campaign on her political expertise (Hoffmann, Reference Hoffmann2018, p. 66). At the same time, the team questioned Trump’s moral integrity, yielding a consistently large number of negative propriety evaluations throughout the entire online campaign (Hoffmann, Reference Hoffmann2018, p. 72). In contrast, in the 2020 Democratic Twitter campaign, Biden’s election team was actually able to directly attack the governing party, namely the Republicans. It is thus not surprising to find that positive self-praise of Biden’s ambition to change current politics is often dovetailed to negative capacity evaluations, criticising Trump’s presidential decisions (see Example 12). The upshot of this campaign strategy is that Joe Biden is characterised as an active, motivated contender who is about to bring change to a dysfunctional administration (see also Section 8).

Compare these findings to the use of negative judgment evaluations on Donald Trump’s Twitter account during the main election phase from July to October 2020 (see Figure 4.8). Trump makes more flexible use of different judgment subsystems. Most dominant are capacity, propriety and veracity evaluations, with tenacity evaluations in fourth place and normality evaluations appearing in much smaller numbers. It is notable that capacity and propriety evaluations first decline from July to August 2020 and then gradually increase toward the end of the election campaign. Tenacity evaluations equally trail along this path but, in contrast to propriety and veracity evaluations, peak in early September 2022.

Figure 4.8 Temporal dispersion of negative judgment evaluations on @realDonaldTrump during the US presidential election campaign 2020.

In Figure 4.9, we can see the use of negative judgment evaluations by Trump’s Twitter team in the online election campaign of the US presidential elections in 2016. Note that Trump’s Twitter team employs more veracity evaluations in 2022 than in 2016 (cf. Hoffmann, Reference Hoffmann2018). One reason for this could be that Trump – as governing president – was forced to account for his decisions and fight off criticism more frequently than in 2014, when he was merely considered a presidential candidate. Figure 4.10 illustrates the large number of targets of negative judgment evaluations that Trump chose to attack in 2020. It includes various media outlets, Democratic politicians, actors, academics and intellectuals or government officials.

Figure 4.9 Temporal dispersion of negative judgment evaluations on @realDonaldTrump during the US presidential election campaign 2016.

Figure 4.10 Targets of negative evaluation on @realDonaldTrump during the US presidential election campaign 2020.

When we compare this to the 2016 Twitter campaign, the number of targets for his negative judgment evaluations has widened considerably, and now comprises fellow Republican senators, foreign country officials and even representatives of sports clubs or movie companies or celebrities (see Figure 4.10).

The substantial increase in negative other-evaluations, that are particularly marked by veracity-related claims, including his notorious use of the term ‘fake news’ (see Figure 4.11), is used to repeatedly disqualify and ridicule larger centre-left media outlets, such as the New York Times.

Figure 4.11 Concordance lines of the node expression ‘fake’ in the @realDonaldTrump ETC subcorpus.

In contrast, the targets of evaluation in Biden’s 2020 Twitter election campaign are much more limited, and primarily target Donald Trump or his administration, with very few exceptions. The scope of evaluative targets on Biden’s account (cf. Table 4.3) is compatible with the one by Clinton in the 2016 presidential elections (cf. Hoffmann, Reference Hoffmann2018, p. 76).

While epithets were precluded from the quantitative analysis of this study, the next section takes a closer look at the way these constructions (and related attributive and predicative adjectives) are used to characterise their political counterpart. To this end, the objects of evaluation will be considered in more detail for both politicians in question, since they are likely to broaden and contextualise our understanding of the quantitative results we have discussed.

8 Reflexive Image Building on Twitter

In this section, we will take a closer look at the objects of evaluation used by both presidential candidates to describe each other in their online election campaign on Twitter in 2020. Such negative attributions reveal what both political camps consider to be unfavourable personality traits, so that the opposite characteristics are, by implication, regarded as virtuous characteristics and implicitly ascribed to the candidates themselves. Objects of evaluation thus provide a decisive map to the ideological framework on which both (Democratic and Republican) election campaigns rest. The evaluative descriptions commonly take the form of attributive or predicative adjectives (see Figures 4.12 and 4.13).

Figure 4.12 Adjectives with negative polarity used to describe Joe Biden, capacity/tenacity (grey); propriety (black); @realDonaldTrump, ETC subcorpus.

Figure 4.13 Adjectives with negative polarity used to describe Donald Trump, capacity/tenacity (grey); propriety (black); @JoeBiden, ETC subcorpus.

In Figure 4.12, we can see that Trump frequently employs both tenacity/capacity and propriety evaluations when attacking Biden’s personality. He dominantly targets Biden’s physical and psychological characteristics, suggesting that both might be interrelated. Instead, Biden’s choice of objects of evaluation centres almost exclusively on the moral dimension of Trump’s character (propriety-related attributions), with a few capacity-related attacks. When compared to the presidential election campaign in 2016, Biden’s current profile of adjectival Trump attacks seems very similar (cf. Hoffmann, Reference Hoffmann2018, p. 77). In contrast to Clinton’s 2016 online Twitter campaign, however, Biden’s campaign team uses negative propriety evaluations much less frequently in the 2020 election campaign. The resulting evaluative ‘gap’ is often surprisingly filled with descriptions of a different kind: Biden’s Twitter campaign team frequently characterises Trump, using capacity-based attributions, such as ‘wealthy’ and ‘well-connected’, stressing the opponent’s privileged social background. Without context, such attributions should be considered as positive evaluations. However, we must take the context into consideration: Wodak (Reference Wodak2020, p. 94) explains that in far-right discourse ‘an internal distinction and opposition between the rural and pure heartland and decadent, corrupt cities or the capital are constructed’. This division separates a fictional community of poor, hard-working people from the rural midwest from a rich and decadent elite in the large US metropoles (cf. Richardson & Wodak, Reference Richardson and Wodak2009). Within this ideological framework, being called ‘rich’ and ‘privileged’ is not something Trump wishes to be associated with, and the polarity of the evaluative expressions is reversed.

By using these descriptions, Biden feeds into Trump’s own alt-right narrative of poor against the rich, attempting to re-frame it against Trump. At the same time, Biden is being staged as the actual representative of ‘ordinary US working-class citizens’ (Fetzer & Weizman, Reference Fetzer and Weizman2018; see Example 14), while Trump is sketched as a powerful self-centred, eccentric New Yorker. In the same vein, Biden exploits his allegedly ‘rural’ upbringing in small town Philadelphia, stressing his devotion to create new jobs for regular ‘folks’ (see Example 15).

This strategy, that couples negative other-evaluations with positive self-evaluations, clearly deviates from Clinton’s 2016 Twitter campaign that hoped to capitalise on decades of political experience in Washington. What we see here is a strategic shift from Clinton’s propriety-related attacks to Biden’s strategy of exploiting positive self-representations to re-frame the alt-right narrative on which Trump’s election ultimately rests. It is likely that this shift may have contributed (among other perhaps more significant factors) to tipping the scale in favour of the Democratic presidential candidate on Election Day 2020.

9 Conclusion

This study set out to capture evaluations in the two official Twitter accounts of the Democratic and Republican candidates for the US presidential elections in 2020. It could be shown that a blend of semantic annotation tools (USAS semantic tagger) and manual, context-based codings can supplement existing methods to capture the evaluative profile of mid and large size text corpora. More importantly perhaps, it was shown that the diachronic use and dispersion of negative evaluations in Joe Biden’s and Donald Trump’s election campaign tweets are in large parts consistent with the use of negative evaluations in previous Twitter election campaigns (Hoffmann, Reference Hoffmann2018).

Some notable differences could, however, be found: for Trump, the targets and objects of evaluation seem to have broadened, reflecting his attempts to repeatedly counter attacks and criticism from a wide array of social and political individuals and groups, even within his own political party. It shows that Trump was forced to defend himself and his political decisions in 2020, while Joe Biden found himself in a position to challenge official government policies. The situation was reversed in the US presidential elections in 2016. Joe Biden did not win the presidential election in 2020 solely because he used a specific collection of negative evaluations, nor did Trump lose it because of the way he discredited his contender. It seems more likely that Biden managed to balance (and connect) the use of negative and positive evaluations more successfully in 2020 than Hillary Clinton did in 2016.

While four years earlier, ‘Trump and his team appear to have [repeatedly] struck a balance between using Twitter for criticism and promotion’ (Clarke & Grieve, Reference Clarke and Grieve2019, p. 20), in 2020 the Democratic election team have increased their efforts to level the playing field. The study provides evidence for this view and further shows the need and relevance of researching evaluation to uncover the persuasive effects of political and other types of persuasive discourse (also demonstrated, e.g., in Decock & Plevoets, this volume).

1 Introduction

Social engagement and interaction are increasingly taking place through new and advanced forms of online communication. More and more of these interactions involve complex processes of persuasion and influence (Dey et al., Reference Dey, Duff, Karahalios and Fu2017; Nguyen, Dabbish, & Kiesler, Reference Nguyen, Dabbish and Kiesler2015; cf. also Hoffmann, this volume; Decock & Plevoets, this volume; Heritage, this volume; Lawson, this volume; Dance, this volume). Persuasion is commonly considered as ‘human communication that is designed to influence others by modifying their beliefs, values, or attitudes’ (Simons, Reference Simons1976, p. 21). Past research has shown that various linguistic features are indicative of an online comment’s persuasion power. For instance, surface-level linguistic cues such as the use of negation, numbers, and certain punctuation marks, can hold a certain persuasion power (Xiao & Khazaei, Reference Xiao and Khazaei2019). The use of discourse relations in online comments can reveal the writer’s reasoning strategy (Peldszus & Stede, Reference Peldszus and Stede2013; Xiao & Conroy, Reference Xiao and Conroy2017) and indicates the persuasiveness of the text (Li & Xiao, Reference Li and Xiao2021). The use of function words in persuasive comments also matters (Humă, this volume; Tan et al., Reference Tan, Niculae, Danescu-Niculescu-Mizil and Lee2016). From a psychological and social perspective, function words reflect how people communicate, whereas content words convey what they are saying. Therefore, function words are much more closely linked to measures of writers’ and readers’ social and psychological worlds (Tausczik & Pennebaker, Reference Tausczik and Pennebaker2010).

Most of these studies are conducted in the context of online discussions such as Reddit (Lawson, this volume; Tan et al., Reference Tan, Niculae, Danescu-Niculescu-Mizil and Lee2016) and Wikipedia discussions (Xiao, Reference Xiao2018). Examples of factors investigated include the norms and rules in the discussions, the user’s status within the discussion forum, and the participants’ prior interactions with other users. Together, these factors influence whether and how a comment in these online discussions is perceived to be persuasive, aside from the language used in the comment. However, online persuasion can occur in non-discussion contexts as well. For instance, people can be persuaded by someone’s personal experiences shared in their online reviews, when reading online blog posts or browsing online news content. The role and importance of persuasive context thus raises some interesting questions. How does context affect the persuasion power of an online text? Are the linguistic indicators of the text’s persuasion power independent of the context? Answers to such questions can help us better understand the influence of the communication context and better interpret the language used in persuasive comments.

As a step towards answering these questions, we examined the linguistic indicators of an online comment’s persuasion power in two different communication contexts that are non-discussion based. The first one presents standalone online argument pairs from the dataset developed by Habernal and Gurevych (Reference Habernal and Gurevych2016). The second one focuses on the online review context from Yelp’s Challenge dataset. We then compared the indicators from these two contexts with those that emerge in contexts that are indeed discussion based: the r/ChangeMyView forum from the Reddit platform and Wikipedia’s Article for Deletion (AfD) feature. In the rest of this chapter, we report on relevant work and our data analysis approaches. Next, we compare the linguistic indicators of the online argument’s persuasion power identified in these two datasets. Finally, we discuss how the linguistic features indicative of an online comment’s persuasion power can be leveraged to enrich online communication experiences.

2 Linguistic Indicators of an Online Comment’s Persuasion Power: Literature Review

The linguistic features that mark an online argument’s persuasiveness have been largely explored in the context of subreddit r/ChangeMyView, which is an active subreddit intended for Reddit users who have an opinion on a subject but are open to changing their current view. A user, referred to as the OP (original poster), starts the discussion thread by posting a view. Other Reddit users are then instructed to counter that view with their arguments. When a comment successfully changes an OP’s view, r/ChangeMyView asks the OP to give a delta point (∆) and provide an explanation of why and how the comment has changed their view. This subreddit is heavily moderated, controlling for any posts or comments that do not follow the rules.

The delta mechanism, along with the forum’s moderating rules on how to post and respond in a discussion, provides a unique and valuable place for studying online persuasion. In persuasion studies that are situated in the context of r/ChangeMyView, a comment is labelled as persuasive if it received a delta point and as non-persuasive otherwise. Language analysis of these comments shows that, compared to non-persuasive ones, persuasive comments tend to be longer (Tan et al., Reference Tan, Niculae, Danescu-Niculescu-Mizil and Lee2016), use more words per sentence, and contain more complex words (Xiao & Khazaei, Reference Xiao and Khazaei2019). Additionally, function words and punctuation marks can indicate the persuasiveness of an online comment. For instance, Xiao and Khazaei (Reference Xiao and Khazaei2019) found that in r/ChangeMyView discussions, persuasive comments use more past tense, prepositions, numbers, and punctuation marks. Non-persuasive comments, on the other hand, tend to use more present tense as well as more auxiliary verbs and personal pronouns.

Xiao (Reference Xiao2018) examined the linguistic features indicative of a comment’s persuasiveness in Wikipedia’s Article for Deletion (AfD) discussions. Members of the Wikipedia community collaborate openly to offer an online encyclopaedia. To ensure the quality of its articles, Wikipedia has established community practices to examine and delete inappropriate articles. One such practice deals with the situation when it is not clear what to do with the article. In this case, an online discussion called ‘Article for Deletion’ (AfD) is held for a period of time (often 7–10 days) to encourage people to offer their opinions (e.g., to keep the article). Wikipedia’s AfD policy requires participants to provide rationales to justify their opinion when participating in the discussion, and the final decision is made based on the rationales as opposed to the number of votes for each opinion.

In studying the persuasiveness of Wikipedia AfD comments, Xiao (Reference Xiao2018) considered a comment persuasive if its opinion is the same as the final decision and non-persuasive if opposite. For instance, a comment to delete an article is considered persuasive if the final decision is to delete the article. Otherwise, the comment is non-persuasive. Interestingly, while the length of a comment is a strong indicator of its persuasive power in r/ChangeMyView discussions (Tan et al., Reference Tan, Niculae, Danescu-Niculescu-Mizil and Lee2016; Xiao & Khazaei, Reference Xiao and Khazaei2019), this is not the case in Wikipedia AfD discussions. This implies that the online communication context influences the perceived persuasiveness of a comment and this effect can manifest in the form of linguistic indicators. However, regarding an online comment’s persuasion power, there is no systematic investigation, to our best knowledge, that explores the connection between the contextual influence and the linguistic features in the comment.

In persuasion studies about the language use in comments, researchers in communication/information studies have mainly used the Linguistic Inquiry and Word Count (LIWC) tool. LIWC contains a list of linguistic, social, and psychological categories and the common words that are associated with each category (Pennebaker et al., Reference Pennebaker, Booth, Boyd and Francis2015). The tool calculates the percentage of a category in the input text by counting the number of words in the text that are from the category and dividing it by the total number of words in the text. LIWC has been widely used to gain insights on these aspects from text (Bulkeley & Graves, Reference Bulkeley and Graves2018; Olagunju, Oyebode, & Orji, Reference Olagunju, Oyebode and Orji2020; Salas-Zárate et al., Reference Salas-Zárate, López-López, Valencia-García, Aussenac-Gilles, Almela and Alor-Hernández2014). Consistent with these previous studies, we also use the LIWC tool in the analysis. Furthermore, we focus on exploring the surface-level linguistic features that influence the persuasiveness of the dataset.

3 Non-discussion Context I: The Argument Pair Dataset

We first explore the linguistic indicators in an online argument dataset that was developed by Habernal and Gurevych (Reference Habernal and Gurevych2016). The dataset contains different topics such as banning water bottle use and debating the educational value of a TV show or a book. Each topic has two groups of arguments: persuasive and non-persuasive arguments. The dataset we used has 32 topics that contain 9,111 pairs of arguments in total. These arguments were obtained from two debate portals, namely, createdebate.com and procon.org. Workers through Amazon’s Mechanical Turk annotated the persuasiveness of the arguments. In the annotation task, a worker was provided with both arguments and asked to select the one that is more persuasive. Workers were required to state reasons to justify their choices. The authors applied multiple ways to control annotation quality and consolidate multiple workers’ annotations for an argument pair. They also examined the workers’ own opinions regarding these topics to ensure systematic biases were not in play, since it is known that people’s beliefs affect their judgment of arguments (O’Keefe, Reference O’Keefe1990; Sherif & Hovland, Reference Sherif and Hovland1961; Wolfe & Kurby, Reference Wolfe and Kurby2017). More details on the development of this dataset including the annotation process can be found in the original paper (Habernal & Gurevych, Reference Habernal and Gurevych2016).

4 Non-discussion Context II: Yelp Review Data

Our second exploration is in the context of Yelp reviews. We obtained the review data from Yelp’s Challenge dataset (www.yelp.com/dataset). In this dataset, reviews are not labelled as persuasive or non-persuasive. Instead, each review has the total number of votes it has received for its helpfulness. An online review’s helpfulness ‘facilitates the consumer’s purchase decision process’ (Mudambi & Schuff, Reference Mudambi and Schuff2010, p. 186). That a comment is helpful means that it positively influenced the consumer’s decision-making process, which implies successful persuasion in this context. In fact, many of the findings of persuasion studies are mirrored in helpfulness research, illustrating the strong connection between the two concepts. For instance, the credibility of the author is found to be important both in the perceived persuasive power of the text (Murphy, Reference Murphy2001) and in the perceived helpfulness of the online review (Jin & Liu, Reference Jin and Liu2010; Liu & Park, Reference Liu and Park2015; Weathers, Swains, & Grover, Reference Weathers, Swain and Grover2015). In addition, just as a low-comprehensibility text is perceived to be less persuasive (Murphy, Reference Murphy2001), an online review is also perceived to be less helpful when it bears characteristics of low comprehensibility, such as spelling errors (Ghose & Ipeirotis, Reference Ghose and Ipeirotis2011), low readability level (Cao, Duan, & Gan, Reference Cao, Duan and Gan2011; Gan, Cao, & Jones, Reference Gan, Cao and Jones2012; Huang et al., Reference Huang, Chen, Yen and Tran2015), and/or it is very short (Weathers, Swains, & Grover, Reference Weathers, Swain and Grover2015).

On the other hand, we acknowledge that the two concepts are not synonymous and might differ in certain specialized settings. For instance, Bigne and colleagues (Reference Bigne, Ruiz, Currás-Pérez and Martí-Parreño2020) find that, when focusing on a random sample of Spanish-heavy reviews on a restaurant, there is no strong positive correlation between the definitions of helpfulness and persuasiveness that they adopt in their work. This is not surprising, as randomly sampled reviews are expected to be average in terms of both helpfulness and persuasiveness. We use these findings to inform our experimental design. Rather than randomly sampling reviews from across the helpfulness distribution, we focus on reviews that have been marked as the most helpful by the users themselves. This allows us to focus our analysis where the signal is likely to be stronger.

We process the Yelp data by first sorting the reviews in descending order based on the number of times they were rated helpful. Then, for each business, we identified the most persuasive review – the review that was voted as being helpful by the highest number of users among all the reviews of this business. To eliminate trivial outliers, we eliminate businesses for which the top-rated review had less than 10 votes. Next, we select a non-persuasive review that has (i) not received any votes and (ii) appears before and as close as possible to the top-rated review on the list of reviews hosted on Yelp for this business. The no-votes stipulation is the most important one, as it allows us to pair reviews from the opposite sides of the helpfulness spectrum. The second stipulation is motivated by the fact that users tend to browse the reviews on a business or product in a top-down fashion. Therefore, this stipulation increases the chances that the two reviews have been read by users who read them both and chose to vote for one but not the other. While this is not a prerequisite for our analysis, it is an easy and reasonable step to take. Through this identification process, we obtained 14,140 pairs of reviews for further analysis, with each review pair including a persuasive review and a non-persuasive review for a business.

5 Persuasion Power of Online Comments: Cross-Context Examination

The two previous sections reveal prevalent linguistic indicators of persuasiveness in non-discussion based contexts. In this section, we compare these findings with those that emerge from two discussion-based settings: Reddit’s r/ChangeMyView forum (CMV) and Wikipedia’s AfD feature (AfD). We compare the similarities and differences of the four persuasion contexts at the process, individual, and platform level. At the process level, we consider how the comment’s persuasiveness is evaluated. The individual level explores the effects of persuasiveness on individuals across the four contexts. And finally, we consider how the platform shapes persuasiveness given the four persuasion contexts.

First, we consider persuasiveness at the process level, wherein we find that the four contexts differ in how a comment’s persuasiveness is evaluated. In the AP dataset, two arguments were explicitly evaluated and compared to each other and one was labelled as persuasive and the other non-persuasive. CMV comments were evaluated by OPs in a similar fashion – they read a list of comments and chose one that changed their minds. In the AfD discussion, however, there was no explicit comparison or evaluation of two comments’ persuasiveness. Instead, as explained in the relevant work section, the persuasiveness of the comment was measured based on how its opinion compared with the discussion outcome (Xiao, Reference Xiao2018). In the case of Yelp reviews, the persuasion power of a review was evaluated based on its perceived helpfulness. A helpful text is one that has influenced the reader to make an informed decision regarding the product or service. Since the helpful text ‘influences’, it is considered persuasive. From the persuasion process perspective, all four contexts have one thing in common. Specifically, according to the elaboration likelihood model (ELM) of persuasion, developed by Petty and Cacioppo (Reference Petty and Cacioppo1986), one’s attitudes can be changed through either central or peripheral routes. In the central route, one carefully considers the presented information on the matter, whereas in the peripheral routes the individual focuses on the contextual information. When an individual is presented with a persuasive message and is sufficiently motivated and able to process it, a central route is more likely to be used. An individual is ‘sufficiently motivated’ when the message is considered important to the individual and ‘sufficiently able’ when they are mentally capable and physically available to process and evaluate the message. Thus, at the process level, all four contexts seem to evaluate comments mainly through the central route because of the focus on the content of the comment.

Second, the four contexts vary in the expected behavioural outcomes of successful persuasion at the individual level. Miller (Reference Miller, Dillard and Shen2013) suggested three different behavioural outcomes after a person is successfully persuaded: view establishment, view reinforcement, and view change. In a view establishment situation, one does not have a pre-determined view or attitude and only establishes one after the persuasion process. In a view reinforcement situation, one’s pre-existing opinion or attitude is reinforced after the persuasion process. In the third situation, view change, one is persuaded to change their pre-existing view or attitude to something different or opposite. As mentioned in the relevant work section, in AfD discussions the person who makes the final decision is expected to review all the participants’ comments and makes the final decision based on their reasoning instead of the majority vote of the opinions. From this perspective, the persuasive power of an AfD comment contributes to the view establishment of the individual. In CMV discussions, the original posters (OPs) identify the comments that have persuaded them to change their original views. The persuasive comments therefore contribute to the view change of OPs. In the Yelp review situation, the consumer often has a pre-existing view or attitude prior to reading the reviews (Li & Zhan, Reference Li and Zhan2011). Therefore, the persuasion power mainly reinforces one’s purchase decision or changes one’s mind. In the case of the Argument Pair (AP) dataset, the situation is probably more complicated, as there is no prior assumption of the reader’s pre-existing view so the persuasion power may contribute to all three possible outcomes.

Third, we consider the four communication contexts at the platform level. Unlike the other three contexts, AfD participants have a collective identity – they are Wikipedians. There is a strong sense of community among them such that they are expected to follow Wikipedia policies in terms of how to participate and offer their reasoning, and share a collective goal: to maintain and improve the quality of Wikipedia articles. This influences the persuasion processes. For instance, users’ usernames and status are more easily recognized, and thus, they are expected to play a more significant role in the persuasion process (Xiao & Xiao, Reference Xiao and Xiao2020). This is different from Yelp, where the sense of community is based on review contributions but not based on knowledge of one another (Parikh et al., Reference Parikh, Behnke, Nelson, Vorvoreanu and Almanza2015). A similar argument can be made for the Argument Pairs and Reddit CMV discussions. The comparison of the four contexts is summarized in Table 5.2.

In Table 5.3, we present the linguistic indicators that are identified from at least two of the four contexts. The indicators for CMV and AfD discussions are obtained from the literature (Xiao, Reference Xiao2018; Xiao & Khazaei, Reference Xiao and Khazaei2019).

As shown in Table 5.2, the contexts of CMV discussions, Yelp reviews, and AP arguments seem to be more similar than Wikipedia AfD discussions. Interestingly, the three contexts have more overlapping indicators such as the length of a text and the use of punctuation marks (see Table 5.3). These are mainly related to the sophistication and comprehensibility of the text. Literature suggests that the length of a text (Crossley & McNamara, Reference Crossley and McNamara2012) and lexical difficulty and diversity (Graesser et al., Reference Graesser, McNamara, Louwerse and Cai2004) can be used to measure language sophistication. According to Mensah, Xiao, and Soundarajan (Reference Mensah, Xiao and Soundarajan2019), variations in language (e.g., sophistication of the text) can affect readers’ judgments of the author’s credibility. Furthermore, lexical difficulty is directly related to the readers’ judgments of the author’s competence and socioeconomic status based on the preference for complexity principle (Hosman, Reference Hosman, Dillard and Pfau2002). It is therefore possible that comments with these characteristics are perceived as more credible because the authors have higher perceived competence or education. At the very least, the characteristics may show that the participants have put more intellectual effort in the discussions and are therefore perceived, at a superficial level, to be more credible. Therefore, we speculate that the significance of these linguistic indicators reflects the influence of the contexts on the comment’s perceived credibility.

This interpretation also helps explain why AfD discussions show different linguistic patterns from the other three. Because of the strong sense of community, Wikipedia participants have various ways to establish their credibility in the community (e.g., different discussion forums in the same community, editing, administering). Long-term members, for instance, have usernames that substantially influence their perceived credibility. The text’s sophistication and comprehensibility is therefore one of the many ways to help establish the writer’s credibility. In addition, Wikipedia participants are expected to seriously engage in the discussions and provide their thoughts since they have a collective goal in the process. Therefore, the perceived intellectual efforts are similar regardless of the comments’ views, that is, the same as or opposite to the final decisions. These linguistic features are therefore not perceived to be that useful in differentiating persuasive comments from non-persuasive ones. Interestingly, quantifiers can be used to indicate a comment’s persuasion power in all four contexts. Prior literature shows that using quantifiers instead of descriptive modifiers provides integrity to the communication (Yalch & Elmore-Yalch, Reference Yalch and Elmore-Yalch1984). Even though some earlier studies showed negative effects of quantification on persuasion when the source is of low credibility (mainly advertisements) (Hosman, Reference Hosman, Dillard and Pfau2002), the fact that quantification is positively associated with persuasion in all the four online contexts implies the importance of using numbers in persuading an online audience. This observation also speaks to the challenge and importance of detecting misinformation and disinformation in online contexts, as they can be very persuasive and influential to the receivers.

Of the three contexts, CMV discussions and the AP dataset seem to be more similar than Yelp reviews (Table 5.2). This is also supported by how much their linguistic indicators overlap with each other (Table 5.3). A closer look at these linguistic indicators suggests that, while it is important to the perceived persuasion power in CMV discussions and in online argument pairs whether the comment uses complex words or sophisticated sentences, it does not seem to be the case in the Yelp review context. Ismagilova, Dwivedi, and Slade’s (Reference Ismagilova, Dwivedi and Slade2020) experiments suggest that perceived reviewer rationality has a positive effect on the perceived influence of both online product and service review. Yet, Li et al.’s (Reference Li, Zhang, Zhou and Zhang2016) linear regression analysis of the Yelp restaurant reviews suggest that a review perceived as helpful may not provide more detailed and valuable information on the restaurant. Additionally, research suggests that the main intention to read reviews was to reinforce purchase decisions (Li & Zhan, Reference Li and Zhan2011). Based on the persuasion literature, such pre-existing views regarding the business can affect judgments of the reviews such that the analytical aspect of the review is not as important as in the other two contexts. Specifically, one’s assessment of a persuasive comment is influenced by their position on the topic (O’Keefe, Reference O’Keefe1990; Sherif & Hovland, Reference Sherif and Hovland1961). When the proposed comment is about something that the person finds acceptable, then the person subconsciously minimizes the differences between the commenter’s position and his or her own position (assimilation effect), and vice versa (contrast effect).

Xiao’s (Reference Xiao2018) analysis shows that AfD persuasive comments tend to have more words and phrases related to seeing. On the other hand, it shows the effect size of that language indicator is very small (0.04) and the use of personal pronouns is not a significant indicator of a comment’s persuasion power. We notice that the way the word see is used in AfD discussions is not necessarily about one’s personal experiences (e.g., seeing things). For instance, we note that participants tend to use the word see when referring to Wikipedia policies in the discussion using phrases such as ‘see WP:FORBESCON’, ‘See WP:POLOUTCOMES’. There is a tangible artifact, that is, the article that the discussion is focused on. Participants also tend to use the word see when referring to specific aspects of the article, for example, ‘The only reliable source dealing with him I’ve seen so far is the one that says he didn’t exist’, ‘If this stays, I would like to see some independent sourcing’, ‘I’d love to see some significant coverage in RS.’ Additionally, the discussion is about the decision to be made regarding the article. Participants use the word see when offering their views related to this process and outcome, as in ‘I see no indication that this passes GNG’, ‘from what I see it should be speedy [sic] deleted’. Lastly, even if the participants were sharing their personal experiences in this discussion forum (e.g., past experiences in AfD processes), they are probably perceived as important as those in the Yelp review situations are when the comments are being evaluated. As illustrated in Xiao and Askin’s (Reference Xiao and Askin2014) analysis of the AfD arguments, precedence was a relatively little cited justification compared to others. The authors explained that this reflects the influence of Wikipedia’s policies and expectations regarding AfD discussions. One of the most often cited sections of Wikipedia’s ‘Arguments to avoid’ page is ‘Other stuff exists.’ Essentially, this page argues that a comparison to another article or previous debate is not a sufficient rationale to support one’s argument regarding how to handle the article proposed to be deleted.

6 Discussion

Persuasion literature shows that perceived credibility of the message affects how persuasive the message is (Murphy, Reference Murphy2001). Our finding suggests that in online communications where a writer’s credibility can be established through various platform features (e.g., the status in the online community), language use in the comment plays a less significant role. The linguistic factors of a persuasive online comment are therefore context dependent. In other words, a persuasive language style in one context may not be that persuasive in another. There are at least two implications for the context-dependent nature of persuasiveness on social media. For one, it is more challenging for malicious users to customize and successfully manipulate the perceived credibility of their messages across different social platforms. At the same time, it may be challenging for the general public to discern the various language styles that are persuasive in different social media channels. We therefore envision a social media feature that raises people’s awareness of the linguistic features that carry persuasion power in that specific platform.

According to the persuasion knowledge model by Friestad and Wright (Reference Friestad and Wright1994) and the modified model for social media communication by Xiao (Reference Xiao, Luttrell, Xiao and Glass2021), people’s persuasion knowledge includes their understandings of the persuasive power of some psychological activities among other various aspects. People also develop persuasion knowledge over time as they consciously participate in persuasion episodes. In these conscious experiences, people need to recognize persuasion tactics, the reason they are used, and assess how effective they are. From the perspective of a persuasion knowledge model, we expect that the provision of such a persuasion awareness feature on social media would help people (i) accumulate their persuasion knowledge through extended use and (ii) become more critical over time when evaluating online messages.

Nurturing one’s persuasiveness awareness can be a double-edged sword. It can help users compose comments that are more persuasive and that better interpret and evaluate comments posted by others. However, the introduced persuasiveness awareness capability could have an adverse effect in three main ways. First, knowing that the comment has low persuasive power, the user may decide to manipulate the rhetoric to make it more persuasive. This may increase the chance that the comment successfully persuades other users, but it is not due to the facts or evidence or logical connections between the premise and the conclusion. This can be detrimental if the comment itself is not actually a valid or factual argument. Second, novice users with limited language ability may be de-motivated to participate in the online discussions when they become aware that their comments have much less persuasive power compared to the other participants. A negative outcome of this situation is that the other participants could then monopolize the conversation. In addition, as seen in a prior study on the effects of knowing others’ rationales in a group activity, this can add the risk of groupthink (Xiao, Reference Xiao2013). Third, would this awareness bring additional risks to the participants if used over time? For example, consider a long-term member of an online discussion forum who is always active in the discussions and now often finds out that their comments are considered not persuasive. Would the member become depressed or lose confidence or comfort in participating in the discussions? As much as online persuasion processes and mechanisms and detection of persuasion power are being explored, we call for research that investigates the effects of one’s persuasion awareness in online communications.

7 Conclusion

Participation in online communications can be anonymous, asynchronous, and open to any internet user or registered community member. While this makes it relatively easy for people to join and offer their opinions, it can be quite challenging to interpret and evaluate others’ comments. At the same time, complex interactions such as persuasion and argumentation are increasingly becoming common in online communications (Heritage, this volume, Lawson, this volume; Tan et al., Reference Tan, Niculae, Danescu-Niculescu-Mizil and Lee2016). In response, researchers are investigating online persuasion phenomena to identify the linguistic indicators of an online comment’s persuasion power. Most of these studies are situated in the context of online discussion forums. However, it is unclear whether and how these communication contexts affect the perceived persuasion power of the comments. In this study, we analysed the linguistic indicators of an online comment’s persuasion power in two communication contexts: standalone argument pairs and Yelp reviews. Together with two online discussion contexts (Wikipedia Article for Deletion discussions and subreddit r/ChangeMyView), we conducted a cross-context examination that yielded similarities and differences across the four contexts. We found that the linguistic factors of a persuasive online comment are context dependent. Different online communication contexts may affect the linguistic features of a comment’s persuasion power as well as shape perceived persuasion and persuasion awareness in online communication contexts. These insights can be leveraged to enrich online communication experiences.

1 Introduction and Rationale of the Study

In face-to-face (F2F) communication, positive and negative emotions and attitudes can be expressed and emphasized through para-verbal (e.g., tone, volume) and non-verbal (e.g., facial expressions) means. Communicators try to simulate this multimodality of F2F communication in written Computer-Mediated Discourse (CMD) by using alternative paralinguistic devices such as capitalization (i.e., use of uppercase letters), flooding (i.e., deliberately repeating) of exclamation/question marks, and emoticons or emoji (Androutsopoulos, Reference Androutsopoulos, Kristiansen and Coupland2011). Studies have found that the use of such alternative paralinguistic cues is helpful in correctly interpreting the senders’ emotions and attitudes and that they indeed influence the perceived strength of these emotions and attitudes (Harris & Paradice, Reference Harris and Paradice2007; Sampietro, Reference Sampietro2019; Xu et al., Reference Xu, Chen and Liu2017). However, the use and impact of these alternative paralinguistic CMD-features (henceforth referred to as APF) cannot simply be equated with the use and impact of their para- and non-verbal counterparts in F2F communication. Indeed, as Glikson et al. put it with regard to the smiley emoji: ‘a smiley is not a smile’ (Reference Glikson, Cheshin and van Kleef2018, p. 614) in the sense that a smiley is used differently and has different effects on the recipient compared to a smile. Against this background, this chapter sets out to explore APF in online hotel reviews on Booking.com and how these features influence reply strategies in hotel management responses to these reviews.

We aim to examine the use and impact of APF in online hotel reviews through the theoretical lenses of normativity (i.e., ways of evaluating, judging, and policing semiotic practices, Leppänen et al., Reference Leppänen, Møller, Nørreby, Stæhr and Kytölä2015) and rapport management (i.e., ‘the use of language to promote, maintain, or threaten harmonious relationships’, Spencer-Oatey, Reference Spencer-Oatey2008, p. 3), two theoretical concepts that are highly relevant in this context for the following reasons. First, addressing normativity is crucial in view of the pluralization of written language norms (Androutsopoulos, Reference Androutsopoulos, Kristiansen and Coupland2011). The present-day era of ‘Late Modernity’ (Giddens, Reference Giddens1991) is characterized by a strong informalization of written (digital) discourse, which is also reflected in the spread and functional elaboration of APF. In spite of this tendency towards more informal language in written (digital) communication, however, there are considerable differences in the ways these features are used and tolerated. Indeed, different styles of writing are ‘deemed appropriate in different environments and genres and to different user groups’ (Androutsopoulos, Reference Androutsopoulos, Kristiansen and Coupland2011, p. 11). As a necessary step to further explore this claim of situated normativity with regard to APF, we aim to describe the use of APF in online hotel reviews and business responses in terms of different types of APF and their frequency patterns.

Second, in their capacity of intensifying positive or negative emotions and attitudes (Liebrecht et al., Reference Liebrecht, Hustinx and van Mulken2019), APF can be employed both to promote and to threaten rapport (i.e., a harmonious relationship) and social cohesion between interactants. Their use may thus affect the recipient’s feelings towards the person who used the features as well as the recipient’s response. In the fields of digital communication and marketing, the relational effects of the use of positive emoji have already been studied, showing that positive emoji lead recipients to experience higher positive affect through emotional contagion (Das et al., Reference Das, Wiener and Kareklas2019; Smith & Rose, Reference Smith, Rose, Geuens, Pandelaere, Tuan Phan and Vermeir2018). The relational effects of other APF have – to our knowledge – not yet been examined, however, nor have their effects been explored when they are used to strengthen negative instead of positive emotions. Moreover, these effects have only been examined with regard to recipients’ attitudes, not with regard to the ways in which they respond. It is thus a valuable endeavour to examine the rapport-related effects of these features in written CMD, and the extent to which these effects depend on the frequency of use, and emotional valence (positive vs. negative). In doing so, this study picks up on recent research in pragmatics which makes the case for improving the empirical foundations of theories on politeness and rapport management by also taking into account the effects of language use on interactants (i.e., a focus on perlocution) (Decock & Depraetere, Reference Decock and Depraetere2018).

As already mentioned, we will explore the use and impact of APF in the genre of online User-Generated (UG) hotel reviews on Booking.com as a form of Electronic Word-of-Mouth (eWOM). Apart from reviews’ growing societal importance as publicly available persuasive texts influencing consumers’ travel-related purchase decisions (Fotis et al., Reference Fotis, Buhalis, Rossides, Fuchs, Ricci and Cantoni2012), making it a high-stake genre, this genre was chosen for the following reasons.

First, the specific characteristics of online review (management) make it possible to conduct a highly systematic cross-valence analysis of the use and impact of APF. As a first characteristic, online hotel reviews contain positive and/or negative feedback on a guest’s hotel experience. This means that the genre serves to express both positive and negative emotions and attitudes. As a second characteristic, popular hotel review platforms such as Booking.com allow for only limited interaction to take place: hotels are allowed to write no more than one response to each review, and no subsequent interaction is possible, meaning that every guest-hotel interaction consists of one guest review and one hotel response.

Second, we can offer a novel approach to research on online review (management). APF have mainly been discussed in contexts of private messaging (e.g., Hilte, Reference Hilte2019; but see Seghers et al., Reference Seghers, De Clerck and Lybaert2021). It is timely to also examine them in online review (management) as a form of public CMD, as it is to be expected that the shift in audience (from one-to-one to one-to-many) as well as the professional context go hand in hand with a specific set of norms governing their use, impact, and evaluation (Xiao et al., this volume). Moreover, previous research on online hotel reviews is characterized by a rather one-sided focus on (responses to) negative reviews (Cenni, Reference Cenni2022). Positive reviews and mixed reviews have received less scholarly attention (Hoffmann, this volume). This calls for the adoption of a cross-valence perspective to acquire insights into the situated normativity of APF in online reviews and review responses (Androutsopoulos, Reference Androutsopoulos, Kristiansen and Coupland2011). Such an approach is helpful because message valence is known to influence language use. For instance, it has been found that emoji are used more often in positive than in negative messages (Bai et al., Reference Bai, Dan, Mu and Yang2019). In addition, existing linguistic research on online hotel reviews and review responses has described and analysed discourse features, often including the use of APF, in reviews and review responses separately (Ho, Reference Ho2017; Cenni, Reference Cenni2022; Ruytenbeek et al., Reference Ruytenbeek, Verschraegen and Decock2021), neglecting their interactional rapport-related dynamics. This is surprising, as hotel reviews and their responses are two core elements connected with each other in the genre chain of the review-related service encounter. While it is in the interest of hotels to establish or maintain rapport with previous guests in order to avoid or minimize reputational harm, the ease with which this is done is suspected to also depend on the language used in reviews (Zhang & Vásquez, Reference Zhang and Vásquez2014). As such, the presence of APF, which are used to strengthen the illocutionary force of either negative or positive customer evaluations and which may thus have an impact on the addressee’s face and feelings, is likely to influence the way rapport is managed in responses. In addition, this influence might be weaker or stronger depending on feedback valence (positive or negative).

After having discussed the aims and rationale of this study, we will, in the following sections, present our research questions and hypotheses, the methodology we adopted, as well as our findings. We will conclude this chapter with a discussion of our findings, this study’s limitations, and avenues for future research.

2 Research Questions and Hypotheses

Before being able to explore the impact of APF in online reviews on review responses, we first need to know more about their use, hence the first research question (RQ1): Which types and frequencies of APF are found in online reviews, and to what extent do the presence and frequency of these features differ according to feedback valence (positive vs. negative)? Based on the Pollyanna principle, which states there is a universal human tendency to use and expect positive evaluative words (Boucher & Osgood, Reference Boucher and Osgood1969), we hypothesize that APF which strengthen positive feedback will be used more often than APF which strengthen negative feedback (H1).

After having described the types and frequencies of APF in reviews, we will address the following research question (RQ2): What is the impact of APF in online reviews on hotel responses in terms of rapport management, and to what extent does the effect of these features on rapport depend on the frequency of use of APF in online hotel reviews, and feedback valence (positive vs. negative)? We know that APF used to intensify a positive or negative evaluation are indeed perceived as such (Meinders, Reference Meinders2017), and that speech acts whose illocutionary force is strengthened are likely to affect rapport and how it is managed in the ensuing interaction (Spencer-Oatey, Reference Spencer-Oatey2008). Against this background, we expect that a higher number of APF (vs. absence or lower number) used to intensify a positive evaluation will be associated with

• an increased use of rapport-enhancing strategies in hotel responses (H2a)

• and a decreased use of defensive strategies in hotel responses in the case of mixed reviews, namely reviews including both positive and negative feedback (H2b).

Moreover, we expect a higher number of APF (vs. absence or lower number) used to intensify a negative evaluation to be associated with

• a decreased use of rapport-enhancing strategies in hotel responses (H3a)

• and/or an increased use of defensive strategies in hotel responses (H3b).

In the next section, we will present the methodology used to address these research questions and test these hypotheses.

3 Methodology

4 Results

4.2 Influence of APF in Online Hotel Reviews on Hotel Reply Strategies (RQ2, i.e., H2a–b and H3a–b)

H2a, which proposes that a higher number of positive APF is associated with an increased use of rapport-enhancing response strategies, was tested on the subcorpora of responses to entirely positive and mixed reviews. The results reveal that almost all rapport-enhancing strategies remain unaffected by a higher number of positive APF: When more positive APF are used, this does not lead to an increased use of rapport-enhancing response moves, intensifiers strengthening such moves, and it does not lead the hotel manager to highlight more strongly how positive a guest’s review or a guest’s experience was. A higher number of positive APF does have an impact, however, on the way the hotel manager describes their own positive feelings in reaction to positive feedback in that these feelings are then described in a more intensified way. See Figure 6.1 which shows that the (hotel manager’s) description of positive feeling increases when the APF density increases to about 4%. After that, the data become too sparse to confidently estimate the effect. We thus found only limited support for H2a.

Figure 6.1 Effect of APF strengthening positive feedback (density) on the (predicted) frequency of (extreme) descriptions of positive feelings.

H2b, which proposes that a higher number of positive APF is associated with a decreased use of defensive response strategies, is only relevant to the subcorpus of mixed reviews. Bearing in mind that defensive response moves comprise both diminish and deny moves, results reveal no effect of a higher number of positive APF on the frequency with which deny moves are used, but they do reveal an effect on the frequency of the diminish moves and of the intensifiers used to strengthen such diminish moves. Figure 6.2 depicts how the number of diminish moves seems to increase at the beginning when the density of positive APF increases. However, the effect quickly becomes uncertain for a higher APF density. Figure 6.3 demonstrates that the number of intensifiers strengthening diminish moves exhibits a wave-like pattern for increasing density of positive APF: first it increases, then it decreases, but it finally increases again. These findings are not in line with H2b, as we expected a decreased use of defensive response strategies.

Figure 6.2 Effect of APF strengthening positive feedback (density) on the (predicted) frequency of diminish moves in response to negative feedback (in mixed reviews).

Figure 6.3 Effect of APF strengthening positive feedback (density) on the (predicted) frequency of intensifiers strengthening diminish moves in response to negative feedback.

(in mixed reviews)

H3a and H3b were tested on the subcorpora of responses to mixed and entirely negative reviews. H3a proposes that a higher number of negative APF is associated with a decreased use of rapport-enhancing response strategies. Results reveal that rapport-enhancing moves remain unaffected by higher numbers of negative APF. However, we do see an effect on rapport-enhancing language intensification. More specifically, an increasing density of negative APF appears to negatively affect the number of intensifiers for positive moves, as testified by Figure 6.4. Note that this effect is estimated on the data of the mixed reviews alone. However, this effect, which is in line with H3a, only holds for APF density up to 10% after which the effect becomes uncertain (due to data sparsity). Figure 6.5 also shows a general negative effect of APF strengthening negative feedback on the number of intensifiers of accommodating moves: at first the number of intensifiers of accommodating moves slightly increases with increasing negative APF density, but very soon the number of these intensifiers decreases. These results regarding rapport-enhancing language intensification support H3a.

Figure 6.4 Effect of APF strengthening negative feedback (density) on the (predicted) frequency of intensifiers of positive moves.

Figure 6.5 Effect of APF strengthening negative feedback (density) on the (predicted) frequency of intensifiers of accommodating moves.

H3b proposes that a higher number of negative APF is associated with an increased use of defensive response strategies. When testing this hypothesis, we found that a higher number of negative APF has a somewhat mixed effect on the number of defensive response strategies. More specifically, Figure 6.6 shows – in line with H3b – that the number of diminish moves in response to negative feedback begins to increase with a growing density of negative APF, but the effect quickly becomes uncertain. Figure 6.7 shows a mixed effect in that the number of intensifiers for deny moves at first slightly increases with growing negative APF density, but then it clearly decreases until APF density of about 10% after which the number of intensifiers for deny moves increases again.

Figure 6.6 Effect of APF strengthening negative feedback (density) on the (predicted) frequency of diminish moves in response to negative feedback.

Figure 6.7 Effect of APF strengthening negative feedback (density) on the (predicted) frequency of intensifiers for deny moves.

In sum, all these effects indicate no support for H2b and partial support for H2a, H3a, and H3b. Tables 6.6 and 6.7 offer a summary of the results related to our second research question.

Table 6.6 Impact (yes/no) of positive/negative APF on moves in review responses; italics = not in line with hypothesis; bold = in line with hypothesis.

	Moves in hotel review responses
	Rapport-enhancing moves		Defensive moves
	Positive moves	Accommodative moves	Diminish moves	Deny moves
Positive APF in reviews	no (H2a)	no (H2a)	yes (H2b)	no (H2b)
Negative APF in reviews	no (H3a)	no (H3a)	yes (H3b)	no (H3b)

Table 6.7 Impact (yes/no) of positive/negative APF on language intensification in review responses; italics = not in line with hypothesis; bold = in line with hypothesis.

	Language intensification in hotel review responses
	Intensification of rapport-enhancing moves		Intensification of defensive moves		Highlight the guest’s positive feedback
	Pos mov intensification	Accomm move intensification	Dim move intensification	Deny move intensification	Description of review	Description of guest’s experience	Description of hotel management’s feelings
Positive APF in reviews	no (H2a)	no (H2a)	yes (H2b)	no (H2b)	no (H2a)	no (H2a)	yes (H2a)
Negative APF in reviews	yes (H3a)	yes (H3a)	no (H3b)	mixed (H3b)	no (H3a)	no (H3a)	no (H3a)

5 Discussion and Conclusion

Based on the detected types and frequencies of APF in online hotel reviews, we can conclude that they do not occur that often and that they mainly occur in the form of (flooded) exclamation marks. Moreover, we detected significantly more APF in reviews containing only positive feedback than in reviews containing only negative feedback. This latter finding is in line with the Pollyanna Hypothesis, which asserts that there is a universal human tendency to use positive evaluative words more frequently than negative evaluative words in communication, and in line with previous research on the use of emoji (Bai et al., Reference Bai, Dan, Mu and Yang2019). Interestingly, however, when reviewers in our corpus do use APF to strengthen negative feedback, they use flooded punctuation more often than reviewers who strengthen positive feedback, who are more likely to use simple exclamation marks. It thus seems that negative feedback is intensified less often through the use of APF, but when it does happen, it is done in a more extreme way, thus amplifying the negative experience even more. It would be interesting to explore whether this finding holds in other languages, and how it could be explained from a psychological perspective.

After having provided an overview of APF types and frequencies in entirely positive, mixed, and entirely negative reviews, we explored our second research question related to the influence of these APF in online hotel reviews on the ensuing responses: How do they affect response strategies and particularly how rapport is managed in responses? To operationalize what we mean by response strategies, we distinguished between (rapport-enhancing and defensive) moves on the one hand and (rapport-enhancing and defensive) language intensifiers on the other. When unpacking and interpreting the results as presented in Section 4, some interesting patterns emerge.

When first looking at move frequency (see Table 6.6), we see that APF do not have an impact on the number of positive, accommodative, and deny moves in responses, which runs counter to what we expected, but APF did affect the frequency of diminish moves: both a higher number of positive APF and a higher number of negative APF are associated with higher numbers of diminish moves. While we expected this more defensive stance in reaction to the use of negative APF, we did not expect this in reaction to positive APF. A possible explanation for this result, which is surprising at first sight, may lie in the fact that defensive response strategies, and especially diminish moves, tend to be formulated in such a way that they may not necessarily come across as impolite or offensive. The review management company’s response policy stipulates that impolite and aggressive responses should be avoided at all times because they are considered unprofessional, and unprofessional behaviour is not in the interest of hotels, who want to avoid or at least minimize reputational harm. Diminish strategies can thus be characterized as defensive strategies in that they try to mitigate the complaint in an effort to defend a hotel’s reputation, but with a potentially accommodative feel to them (see, e.g., the move ‘suggest or recommend’ in Table 6.1). In that sense, one could explain this result by arguing that a higher number of positive APF in mixed reviews gives a hotel the impression that – given the positive stance of the reviewer – there is room to not hold back in fighting off the criticism in an inoffensive way, thus making the hotel look even better in the eyes of the reviewer and future customers. Overall, when evaluating the results regarding move frequency for entirely positive, mixed, and entirely negative reviews separately, we can conclude that the discourse structure of entirely positive reviews is not affected by APF, while for mixed and entirely negative reviews, the discourse structure is affected, but APF’s influence does not extend beyond diminish moves.

As for language intensification, which we subdivided into intensifiers of rapport-enhancing and defensive moves on the one hand, and highlighting a guest’s feedback on the other, we found that positive APF in online reviews yielded some unexpected and some expected results (see Table 6.7): (1) they do not influence the use of intensifiers for rapport-enhancing moves, the hotel manager’s description of the review and their description of the guest’s experience (while we expected a higher number of intensifiers for these moves and more intensified positive descriptions), (2) they are associated with more intensification of diminish moves (while we expected less intensification), and (3) they are, as predicted, associated with intensified descriptions of the hotel manager’s positive feelings. The first two findings echo what we found for the moves, and again, the – at first sight – surprising finding regarding diminish moves can be explained by the dual character of these moves, which are defensive in nature without posing a strong threat to rapport by using an accommodating tone. The third finding can be illustrated with the following example, in which a positive review with high APF numbers (We enjoyed it!! Great hotel! Lovely spacious, clean room. Wonderfully decorated!)) receives the following response: ‘Great hotel’ – these words are so nice to hear. We are delighted that you enjoyed a fantastic stay with us – and that you were totally happy with the spacious, clean room. We hope to see you again soon, Kind regards, X’ (our emphasis). This specific type of a hotel manager highlighting a guest’s positive feedback (by referring to the positive feelings caused by this feedback) can be seen as demonstrating emotional contagion. When zooming in on negative APF, we see that they can – as predicted – be associated with less intensification of rapport-enhancing moves, but, contrary to expectations, they did not affect the intensification of diminish moves. Their effect on the intensification of deny moves is mixed, which makes it hard to interpret from a quantitative perspective.

When taking a bird’s eye perspective on these results related to the impact of APF in reviews on hotel management responses, they reveal some clear patterns, allowing us to formulate the following conclusions: First, as we often found no impact on specific reply strategies, we can conclude that APF’s influence on how review-related interactions unfold in terms of rapport is quite subtle. This subtle influence may be due to the highly professional setting in which the review responses in our corpus are created (see Section 3.1). In this setting, there is a certain gold standard of what responses to reviews should look like, with rather fixed generic conventions (Cenni, Reference Cenni2022), and this gold standard also requires hotels to remain professional in their behaviour at all times, and thus to avoid emotional excesses and impoliteness in their interactions with guests. Second, it is remarkable that, although negative APF are less frequently used compared to positive APF, they do seem to have a stronger impact on responses, as they are associated with less intensification of rapport-enhancing moves and a higher frequency of diminish moves. This can be interpreted as an affirmation of the negativity bias, which refers to a person’s bias to automatically pay ‘more attention to unpleasant (negative) than to pleasant (positive) information’ because negative information is marked (Liebrecht et al., Reference Liebrecht, Hustinx and van Mulken2019, p. 172). Third, the fact that diminish moves increase in reaction to both positive and negative APF testifies to their dual character of being defensive, but with an accommodating potential. Overall, it seems that a higher frequency of positive APF leads to a more enthusiastic and more persuasive stance in responses to these reviews, and that a higher frequency of APF strengthening negative feedback leads to a more defensive, less rapport-enhancing stance in responses to these reviews.

By revealing differences in the use of positive and negative APF in online reviews as a type of public CMD, this chapter contributes to and confirms the observation of situated normativity in online written discourse. Our results also shed light on differences between APF as used in online reviews (see RQ1) and APF as used in responses to these reviews (see Table 6.1), an issue which we did not explicitly discuss as it would have gone beyond the scope of our research questions. Future research can compare our findings with APF as used in different forms of private and public CMD to acquire further insights into the norms governing the use of these features.

Our approach in studying the relational effects of APF was novel in that we analysed their effects beyond emoji and beyond the intensification of positive emotions, and by looking at their rapport-related impact from an interactional perspective. In doing so, we were able to show that the language used in reviews is not without consequence in terms of building rapport and makes certain reply strategies more likely than others.

This study obviously also comes with several limitations. As an additional way of assessing rapport management, we could have supplemented our quantitative analysis with a qualitative component, delving deeper into certain phenomena we observed, and we could also have looked more deeply into processes of accommodation with regard to language style: To what extent does the use of APF also trigger the use of APF on the part of the hotel manager? To what extent does brand identity and the type of formal or informal communication style that comes with it outplay the principles of language style accommodation in this specific context? These are all issues which can be explored in future research. Moreover, the type of quantitative corpus analysis we performed can reveal associations between certain features, but it cannot make claims about causality, which would enable us to exclude other explanations for our findings. It would therefore be interesting to test the second research question on the impact of APF experimentally. Finally, as additional avenues for future research, it would be worthwhile to explore this study’s research questions using similar data in other languages or on other platforms and using different types of consumer-company data on other platforms.

1 English as a World Language and Persuasion

English is the most widely spoken language in the world, considering not only first language speakers, but also its use as a second language and as a lingua franca. Estimates suggest that more than one in four people globally are capable of communicating in English (Crystal, Reference Crystal2003, p. 69; Kachru, Reference Kachru, Filppula, Klemola and Sharma2017, p. 272). Among those who speak English, second language and lingua franca speakers outnumber first language speakers (Seidlhofer, Reference Seidlhofer, Dziubalska-Kołaczyk and Przedlacka2005, p. 59). The widespread use of a single language is arguably a boon to international unity and exchange because it enables direct communication between counterparts who would otherwise need to rely on translators and interpreters, greatly complicating such exchanges, while reducing their effectiveness.

However, international communication through a single, shared language is not necessarily quite as seamless as this optimistic view might suggest. Use of the English language in international exchange might enable direct communication but also complicates it (Berns, Reference Berns2008; Smith & Nelson, Reference Smith, Nelson, Nelson, Proshina and Davis2019). Such complications arise because the English language is not simply a unitary and universal form of communication, which speakers and writers rely on to communicate. Rather, individuals speak English at varying levels of proficiency, and, more importantly, rely on a richly differentiated set of dialects. This diversity has been extensively analysed in research in the field of World Englishes or New Englishes (for a general overview, see Schneider, Reference Schneider2007).Footnote ¹ It covers all levels of the language, including syntax (Rautionaho, Reference Rautionaho2014), lexis (Lambert, Reference Lambert2014), segmental phonology (i.e., phonemes; Meer et al., Reference Meer, Brato and Flores2021), suprasegmental phonology (e.g., speech rhythm; Fuchs, Reference Fuchs2023), and, of particular importance for the present chapter, pragmatics (Collins, Reference Collins2022).

The impact of this diversity on the smoothness of international communication is somewhat mitigated by the fact that some of these dialects, chiefly Standard American and British English, enjoy more international prestige than others, and are hence more widely used and understood (Mair, Reference Mair2013). Moreover, speakers may also enhance mutual comprehension by shifting to such more widely known dialects or accommodate to (i.e., consciously or unconsciously converge with) a particular speaker in a given context (Fang, Reference Fang2017). However, such mitigating strategies alleviate the problem only to some extent. Standard American and British English, notwithstanding their prestige, have substantial but still limited international reach and not everybody is capable of ‘tuning in’ to another dialect or tolerating ambiguity and dealing with subjectively unusual turns of phrase. Hence, even with such accommodations, the considerable variability of how English is spoken across the world seriously limits the seeming effectiveness of the widespread use of a ‘single’ language in international communication.

Across this multitude of dialects of English, also called ‘varieties’ in this field of research, speakers and writers engage in a range of communicative activities and with diverse goals. In many cases these goals will involve what psychologists call persuasion, or the ‘deliberate attempt to change the thoughts, feelings, or behaviors of others’ (Rocklage, et al., Reference Rocklage, Rucker and Nordgren2018, p. 749). Persuasion thus defined is crucial for the management of social relations, a ‘ubiquitous presence in everyday life’ (Humă et al., Reference Humă, Stokoe and Sikveland2020, p. 357) and usually realised through language (Blankenship & Craig, Reference Blankenship and Craig2011, p. 194). Given the fundamental role that language plays in attempts to persuade others, it stands to reason that a linguistic analysis of how such attempts are carried out has the potential to further a better understanding of this psychological and linguistic construct.

2 The Linguistic Analysis of Persuasion

3 Data and Methods

4 Results

The degree of overt expression of persuasion varies substantially within varieties, which was expected, given the inclusion of a wide range of registers. The distributions shown in Figure 7.1 indicate both the spread of values within varieties, as well as the overlap between varieties. At first glance, this might suggest that the degree of overt persuasion is more or less statistically indistinguishable in a cross-dialectal perspective.

Figure 7.1 Overt expression of persuasion across 21 international varieties of English. Thick vertical lines indicate medians, boxes comprise data from the first to the third quartile and the whiskers extend to values up to 1.5 times the interquartile range. Outliers beyond this are shown as dots (some outliers beyond the area of the plot not shown). Varieties marked with an asterisk lack a substantial amount of spoken data from the ICE design.

However, the statistical analysis included register as a fixed factor, such that the systematic variation due to this variable is accounted for.Footnote ⁴ As such, in statistical terms, there are clear differences between varieties, even though, due to the great number of pairwise comparisons, the computation of significance levels is very conservative (see Table 7.3).Footnote ⁵ Generally, varieties placed at either end of the gamut from high-persuasion to low-persuasion varieties differ significantly from most other varieties, except for those that are very close to them in the degree of persuasiveness. For example, KenE (at the top of the range in Figure 7.1) differs significantly from all varieties starting from PakE at the bottom up to HKE but does not differ significantly from the five closest varieties on this distribution. Similarly, PakE (at the bottom of the range) differs significantly from all varieties except SLKE and IndE (see Table 7.2. above for abbreviations for varieties).

The two varieties that differ significantly from just a few others are AmE and TanE. These varieties lack substantial amounts of data in the spoken sections (see Section 3.1). As such, it is likely that were full subcorpora available, differences between these varieties and others would be statistically significant in other cases as well. More generally, while the statistical results (Table 7.3) take account of register and thus the partly sparse data for these varieties, the visual representation in Figure 7.1 does not, and the relative position of these two varieties must be interpreted more cautiously than for the rest of the data.

In terms of geographical patterns, the results reveal that African varieties tend to mostly have higher than average values, followed by Europe/Oceania and the Americas, and finally Asia, with the lowest values. However, there are several exceptions to these generalisations: SAfE has much lower scores for overt expression of persuasion than the other African Englishes, TrinE has higher scores than the other American varieties, and SinE and HKE have much higher values than the rest of the Asian group. In some cases, it is tempting to posit smaller regional groups that appear to be relatively uniform, such as West Africa (NigE and GhE), North America (AmE and CanE), South Asia (IndE, PakE, and SLE) as well as (South-)East Asian city states (HKE and SinE).

5 Discussion and Conclusion

The present study investigated the overt expression of persuasion across 21 international dialects of English from countries where it is used as a first language, or entrenched in society as a second language. In these contexts, new dialects of English have emerged, often in postcolonial contexts, and local standards of English have reached various stages of codification (Schneider, Reference Schneider2007). The linguistic diversity of these World Englishes has been demonstrated in a substantial number of studies, prompting the expectation that the linguistic expression of persuasion might similarly show distinct patterns across the English-speaking world. By using a set of carefully controlled corpora, representing natural language across a wide range of contexts, this chapter also follows calls in the psychological literature for studies on persuasion that investigate its linguistic expression across language at large, rather than relying exclusively on carefully controlled experimental contexts or concentrating exclusively on particular text types (Humă et al., Reference Humă, Stokoe and Sikveland2020, p. 358).

A key finding of this study is that the overt expression of persuasion varies substantially between international varieties of English, with comparatively little overt persuasion found in South Asia, and, at the other end of the distribution, relatively frequent use of overt markers of persuasion in West Africa. These results have important implications for multiple areas of research. While the widespread use of English across many countries in the world enables speakers to communicate with each other, linguistic research has long recognised that diversity of World Englishes and English as a lingua franca can also lead to misunderstandings and miscommunication (Berns, Reference Berns2008; Smith & Nelson, Reference Smith, Nelson, Nelson, Proshina and Davis2019). Previous research has investigated such hurdles to effective communication in terms of phonetic and syntactic variables, among others. However, variation in pragmatics is arguably an equally, or even greater, potential source of miscommunication because interlocutors might be less attuned to variation in how pragmatic meaning is expressed by the other party. For example, the very frequent expression of persuasion in West African Englishes could potentially be perceived as inappropriately forthright or demanding by speakers of South Asian Englishes, where persuasion is less frequently overtly expressed. Vice versa, speakers of South Asian Englishes might often not deploy linguistic resources for persuasion frequently enough to communicate their position to speakers from high-persuasion dialects of English. Against the fundamental role that persuasion and its linguistic expression plays in the management of social relations (Blankenship & Craig, Reference Blankenship and Craig2011, p. 194; Humă et al., Reference Humă, Stokoe and Sikveland2020, p. 357), these findings suggest that speakers using English in international contexts could enhance their communicative effectiveness through increased attention to how, and how strongly, they and their interlocutors express persuasion. Increased sensitivity to the linguistic expression of persuasion could also be of great benefit in English Language Teaching for advanced learners, especially in Business English classes (e.g., Nickerson & Planken, Reference Nickerson and Planken2015).

The present study also demonstrated the useful intersection between MDA and the study of dialectal variation, as pointed out by Biber and Finegan (Reference Biber, Finegan, Biber and Finegan1994, p. 10), and as such contributes to the study of World Englishes and corpus-based dialectometry (Szmrecsanyi, Reference Szmrecsanyi2013), as well as the emerging fields of corpus pragmatics and variational pragmatics (e.g., Anchimbe, Reference Anchimbe2018; Fuchs et al., Reference Fuchs, Gut and Soneye2013; Leuckert & Rüdiger, Reference Leuckert and Rüdiger2021). Furthermore, MDA was applied in this study to a greater number of World Englishes than in previous research. The present results on the degree of overt expression across these varieties at first glance seem to differ from Bohmann’s (Reference Bohmann2019, p. 152) ranking (Europe > Australia/NZ/N America > Caribbean/Africa > South Asia > East Asia), whereas this study arrived at a ranking of Africa > Europe/Oceania > Americas (incl. Caribbean) > Asia. On the one hand, these contrasting findings could be put down to differences in methodology, given that the set of linguistic features used by Bohmann and in this study vary to some extent. Still, there is some overlap between persuasion and stance both in terms of linguistic features and in terms of their conceptualisation as linguistic-psychological constructs. In fact, the results of both studies are likely to be more similar than is immediately visible, mainly because approximately twice as many World Englishes were investigated here. For example, Bohmann includes no African and one Caribbean variety, against six and two varieties, respectively, in this study, suggesting that a high ranking for Africa might be justified and not in contradiction with Bohmann. Apart from this point, the two rankings are relatively similar. Nevertheless, the comparison of individual varieties still reveals two clear differences. Whereas HKE and SinE reach high levels of overt persuasive discourse in the present data, Bohmann’s (Reference Bohmann2019, p. 152) results indicate low levels of explicit stance-marking. These contrasting findings might, in fact, be caused by the afore-mentioned differences in how overt persuasion is measured in the two studies.

More broadly, the perspective adopted in this chapter presented a bird’s-eye view of the overt expression of persuasion. As the discussion has demonstrated, this frame of reference allows for broad comparisons and generalisations on a global basis, in the vein of a limited but growing number of multi-variety studies aiming at broader generalisations and testing models and hypotheses (e.g., Collins & Yao, Reference Collins and Yao2013; Dunn, Reference Dunn2019; Fuchs, Reference Fuchs, Werner, Seoane and Suárez-Gómez2016; Werner, Reference Werner, Werner, Seoane and Suárez-Gómez2016). As such, the present results add to existing evidence for the relevance of areoversals in explaining variation across World Englishes, i.e., the existence of shared patterns in geographically close varieties (Fuchs, Reference Fuchs, Werner, Seoane and Suárez-Gómez2016; Hickey, Reference Hickey2012; Szmrecsanyi & Kortmann, Reference Szmrecsanyi, Kortmann, Filppula, Klemola and Paulasto2009). However, such a broad analysis necessarily precludes a detailed investigation of individual dialects, and which means of linguistic persuasion are particularly prominent there. Such questions could be usefully explored in detailed studies of register variation of a single or a few varieties at a time, focusing on variety-internal variation or on particular linguistic features and how they are deployed by speakers in attempts to persuade (for an example of a useful qualitative approach, see Sorlin, this volume, and Humă, this volume). Moreover, it would also be of interest to determine what variation exists between varieties in how overt expression is expressed linguistically, and what geographic patterns or other explanations for such variation emerge. Finally, to what extent the pragmatic differences in the linguistic expression of persuasion revealed in this analysis lead to misunderstandings and miscommunication cannot be revealed by a corpus analysis of register variation. This question could be addressed through an analysis of corpora of international or cross-cultural communication as well as through dedicated experimental research (see, for example, Xiao et al., this volume).