Introduction: YouTube Comments Interaction

One form of participation in the gaming experience is the posting of public text comments on gaming celebrities’ YouTube video sites. YouTube comments afford fans the opportunity to participate publicly in content creators’ gaming activity as commenters, not just viewers. While the level of participation is not equivalent to that which occurs by actually gaming with Ethan Gamer, as in the Minecraft interaction presented in Chapter 5 (EthanGamer, 2019, May 28), it is more interactive than merely ‘viewing’ the game. Specifically, fans who are located remotely, in a variety of locations, have the opportunity to respond to the YouTube video activity through written conversation. This should in theory also foster interaction with other viewers, which may lead to learning benefits. Yet for this to occur, users need to choose the correct interactional resources, to gain the attention of other commenters and Ethan Gamer himself. On the surface, this is vastly different from television broadcasts, where interaction is a one-way non-interactive process, unless integrated social media resources are made available by broadcasters for this purpose. An example of a more participatory type of interaction experience is current affairs programs such as the Australian Broadcasting Commission’s (ABC) Q+A program, which permits and includes selected Twitter (now X) comments of remote viewers as a component of the broadcast (Q+A, 2008). However, this is only a one way process from an interactional viewpoint, with viewing television audiences and panel members unable to respond to broadcasted tweets unless they are logged. This chapter considers the different levels of participation and interactivity afforded by YouTube comments for children, based on analysis of user comments on two Ethan Gamer videos (EthanGamer, 2015, February 20; EthanGamer, 2020, February 17). This will allow us to understand the capacity for the comments tool to promote collaboration and learning in an additional type of children’s online language and interaction related to gaming.

How Data Was Collected

For the purpose of interactional analysis in the current chapter, substrand comments are the main data source as they allow users to engage in more coherent conversations than the main strand comments (see section below on ‘How YouTube Comments Interaction and Sequencing Work’). These comments include the first post which initiated the substrand, from the main strand sequence. Both main strand and substrand comments were originally collected from Ethan Gamer’s Baby Cow Processor video, (EthanGamer, 2015, February 20), which focuses on Minecraft play. However, only a single substrand was collected from the I Have a Big Belly video (EthanGamer, 2020, February 17). The latter substrand relates to a video which showcases Roblox gaming (see Appendix for details on data collected for this study). It was chosen for its extended nature (104 posts), compared to other substrand sequences, to understand whether length of sequences is likely to be associated with users’ sustained interactive and collaborative activity.

At the commencement of data collection, use of Snipping Tool ensured precise reproduction of comments interaction with full original data, including profile pictures and names. All identifying material was subsequently removed and substituted with pseudonyms for this publication. Examples of comments included in the analysis reproduce de-identified text contributions verbatim and without images, as posted on the specified YouTube comments section of the relevant Ethan Gamer YouTube page. Any comments which are potentially copyrightable have been excluded from the analysis, in keeping with international copyright laws.

Challenges in Creating Pseudonyms for YouTube Comments Users

YouTube permits users to create both a profile picture and a profile name, for which a single pseudonym has been created to preserve participant anonymity in this research. Hence, these components of the comments are not included in the analysis presented for this chapter. However, they may reveal general information which assists us in understanding the online conversations. Specifically, some profile pictures and names reveal whether the user is apparently a child or whether commenters are using adults’ accounts, often of parents, to post comments. As far as profile pictures are concerned, many participants use photographs, apparently of themselves and sometimes of family members. Many, however, do not use photographs at all and use the initial of their first name as a profile picture. These profile pictures appear in larger font than the profile names, within a circle, in a prominent position to the left of each profile name and comment, as in Figure 6.1 (EthanGamer, 2020, February 17).

Figure 6.1 Initials as profile names in YouTube.

Profile names may consist of apparently real names, including first and family names. Many users instead choose nonsensical and humorous names, some of which are inspired by cartoon or gaming characters and a range of popular culture figures. As occurs with nicknames used in other social media and gaming platforms, users choose these profile pictures and names because they reveal an aspect of their identity. It is thus likely that users identify with the chosen characters who become part of users’ persona online. As pointed out by Crystal (Reference Crystal2006), online nicknames may say ‘something about who they are, and act(s) as an invitation to others to talk to them’ (p. 166). Nicknames also provide anonymity for users, which is important for safety, but they may also allow some users to express themselves more freely and even inappropriately, under cover of a fictional identity, sometimes to the detriment of other users.

Where there are real rather than fictional profile names, there is evidence that most users are of English-speaking background. There is also a strong presence of Hispanic and other cultural background names which would ideally be reflected in creation of pseudonyms for this research. There is, however, such a range of user backgrounds and fictional names that it was not possible to reflect such diversity in the pseudonyms. This is also the case where adults’ accounts appear to be used, as gender or cultural background of the actual commenters are unclear. However, in keeping with Conversation Analysis (CA) methodology, such identities are discussed if they are made relevant by commenters in their online talk, as occurs when age is a topic of conversation (see ‘Participants’ Age in Interaction’ section). Findings in this chapter remain relevant regardless of the L1 of participants, nonetheless.

Pseudonyms in this chapter are based simply on the alphabet, for example, ‘User A’ in the analysis and ‘A’ in the extracts. At times, participants address specific other users in the substrand interactions; hence, in such cases the relevant pseudonym (e.g. User C) is used in place of the original name. Letter use for posts in the extracts is alphabetical-chronological, based on the sequence of user posts. Hence, ‘A’ is usually the first poster to whom other users respond in the substrand. The longer substrand with 104 posts (e.g. EthanGamer, 2020, February 17) is, however, distinguished from the other multiple shorter substrands with an asterisk as part of the pseudonym. For example, the first main strand poster is ‘A*’ for the 2020 substrand. Where a specific user posts more than once, a number is added to the letter to signal this for readers, as this assists both analyst and reader in recognizing more active commenters and in understanding the conversation. For example, User A1* is the first commenter who initiates the extended substrand (EthanGamer, 2020, February 17) and responds to other commenters later in the strand. Hence, she is recognizable to readers as a repeat commenter through use of the same pseudonym (User A1*).

How the Analytical Sections Are Organized

The following analytical sections firstly consider how YouTube comments interaction works, as there are a three main options for users. Understanding how these options work assists us in contextualizing and understanding substrand interaction, which is the main focus of this chapter. The focus then shifts to how comments regarding the age of participants assist us in confirming that commenters in the data are in fact children, for whom age appears to be a relevant concern in interaction. Additionally, analysis considers intended recipients of posts and how commenters design their posts accordingly, including techniques for addressing recipients other than the first poster. How commenters design their posts impacts on conversational sequencing and coherence; hence, sequence organization is also discussed briefly. Another consideration in the analysis regards whether the non-standard language used by commenters might be recognizable as that of children, rather than the language of online text interaction in general. This is important also to understand whether age is a recurrent user orientation in these interactions. Other factors include linguistic and interactional features of first posts that prompt substrand discussion, including instances leading to repair and collaborative work, which have potential to promote learning.

How YouTube Comments Interaction and Sequencing Work

The default display of YouTube main comments is ‘Top’ comments rather than ‘Newest’ first. While the system displays many recent comments, they are rarely sequential and appear to be random. The position in the sequence depends on various criteria and is based partly on content creators’ or YouTube moderators’ intervention. For example, content creators may have set up comments as reviewable by themselves, or certain words have been prohibited and hence unacceptable comments deleted (YouTube, n.d.). Users post their comments at various stages of viewing the video; however, there is no detailed time stamp and other commenters only have access to approximate information on when comments have been posted. For example, they can see how many days, weeks, months or years ago they are posted. They would need to select ‘Newest first’ by clicking the ‘sort by’ function, to be able to view the most recent contributions of other participants. Compared with ‘top’ comments the ‘newest’ contributions are in fact reverse chronological with the most recent posts presented first and earliest comments displayed at the bottom. Nonetheless, even these comments appear to be somewhat randomly sequenced.

Users are acutely aware of the non-sequential nature of main strand ‘Top’ comments, as evidenced in Example 6.1, a main strand comment:

User A in Example 6.1 composes and posts a rather lengthy contribution to the comments thread, addressed to Ethan Gamer, about her own work on Minecraft. This post is almost entirely without punctuation, apart from a comma, and concludes with a statement which expresses concern about possibly getting lost in the comments (‘I hope I don’t get lost in the comments’). No substrand is prompted by this comment; however, this and similar comments indicate commenters’ awareness of interactional difficulties of the main strand comments. Only the more private substrand comments provide a sequential ordering of comments to promote user interaction. One aspect which is common to main and substrand comments is that they both occur asynchronously rather than in real time.

To post a comment in the main strand, users are required to sign in before they can use the public comment box which is beneath the video and above the first visible comment (top or newest), as shown in Figure 6.2 (EthanGamer, 2015, February 20).

Figure 6.2 YouTube public comment box.

The newly created post in the main strand appears above the latest top comment. This is quite different from the substrand interaction, which does not require participants to post after the top comment in the list. The ‘reply’ option is in fact available independently of the first post in the main strand, which promotes a chronological sequencing. The first post in these substrands is, however, always a main strand comment to which other users and sometimes the content creator may reply.

Commenters also have the option of ‘liking’ using the thumbs up icon, to positively assess a main strand comment. Likes are frequently elicited in the comments and are a regular component of interaction in these conversations. In addition to the substrand comments, they too constitute an additional figurative type of second pair part of an adjacency pair which relates to the main strand first pair part comment being ‘liked’. There is in fact a correspondence between number of ‘thumbs up’ deployed by participants and length of substrands, with the longest substrands more likely than short substrands to receive numerous ‘thumbs up’ responses. This suggests that main strand comments with the most expressions of approval through the thumbs up icon are more likely to receive multiple substrand responses than those with smaller numbers of ‘thumbs up’ approvals, with some exceptions (see Example 6.9 below). Participants may in fact prefer to use the comments option to articulate their approvals (or disapprovals) of the YouTube video verbally while at the same time using the anonymous thumbs up or down icons. While there are multiple examples of this pattern in the data, the I Have a Big Belly substrand of 103 replies received 148 thumbs up, as presented in Figure 6.3.

Figure 6.3 Display of thumbs up and number of replies at start of substrand.

This entire substrand conversation is affiliative and abounds in colloquial expressions of agreement, in particular ‘Same’, in relation to participants’ long-standing participation in this gamer’s videos. The first post in fact frames the entire substrand conversation, which is dedicated to establishing a common interest in Ethan Gamer’s YouTube gaming videos and nostalgia for Ethan Gamer’s and their own younger days. The affiliative nature of this ‘conversation’ is reinforced by the predominant use of ‘likes’ and absence of ‘thumbs down’.

Participants’ Age in Interaction

While the chosen YouTube videos and games are intended for children, we cannot be sure of the ages of the commenters, who are posting their comments publicly. Furthermore, user profiles are not reliable because children often use adults’ accounts. This is evidenced by the profile pictures and names of adults, which contrast with users’ stated young age or name, which is different to that in the profile name. For example, profile names occasionally include titles such as Dr, which indicate that the account is that of a well-educated adult rather than a child. Profile pictures which show photographs of adults cannot be exhibited here to protect users’ identity. However, they include group photographs, probably of family, single women or men, or single adults with one or more children.

Despite lack of clarity on commenters’ identities, it is appropriate to assume that participants commenting on the videos are approximately of the age group for which Minecraft is officially rated, namely seven to thirteen years, depending on the version of the game (Webwise.ie, n.d). Roblox, on the other hand, suggests an age limit of eight to eighteen (E-SafetyCommissioner, n.d.), which is relevant to the EthanGamer (2020, February 17) rather than EthanGamer (2015, February 20) video. However, the fact that age is a regular orientation in participants’ public interactions on YouTube requires further analytical attention, to better understand children’s online language and interaction.

YouTube commenters often reveal their age in the public conversations, with age and date of birth frequently a topic. There are in fact many posts, both in the main and substrands, where children appear eager to reveal their age. In Example 6.2, user A reveals their birth date and other identifying information, which in this case leads to a strong rebuke by another user.

The date of birth revealed by User A at post 1, in the public main strand, indicates that he lives in India and is approximately ten years old. This can be assumed because the YouTube video and comment were created in 2020 and his declared birth date is apparently 2010 (post 1). User B’s responses are nonsensical or suggest laughter (‘Lel’). User C’s post 5 instead is a request in the form of a negative imperative, without any form of hedging to soften the request, which includes verbal abuse (‘IDIOT’). It is ‘shouted’, as denoted by capital letters, which reinforces the offensiveness of this message, despite the otherwise appropriate advice on revealing identifying information on YouTube.

In Example 6.3, a few users respond to User A’s question on Ethan Gamer’s age.

In post 2, User B1, a repeat contributor, replies that Ethan is eight years old to User A’s question to Ethan Gamer requesting his age. User D (post 4) instead replies to User A as if the question to Ethan Gamer were intended for her and states her age as seven in ‘Me old is 7’. This comment is in non-standard English language despite the profile name denoting English-speaking background and may be due to the developing literacy of the child, who is apparently seven years old. Rather than producing the standard ‘I’m 7’, this user’s post mirrors the syntactical structure of the original question ‘how old are you’ in response. It is ignored by other users in this strand, who do not repair the language used by User D. However, an episode of repair related to content rather than language ensues in regard to post 2. In post 5, User E corrects User B1, who is posting approximately one year later, as the platform permits, and states that Ethan Gamer is now ten, not eight. Given that a response from Ethan Gamer is unlikely in this setting, Users B1 and E’s repairs are collaborative towards User A as they answer his question.

User A1, who prompted the extended 104 post substrand (EthanGamer, 2020, February 17), submits another post in the same substrand when a user expresses agreement and reveals her age.

User A’s post is a substrand reply to User A1*’s original main strand comment ‘Dang, it’s been a long time …’. In post 2, User A1* names User A to indicate that she is being addressed. Naming specific users is a commonly used linguistic and interactional strategy in multi-party chat to promote understanding by signalling the intended recipient. In this substrand conversation, fans reminisce over their past viewings of Ethan Gamer’s YouTube channel, when they were younger. Hence, age is a relevant topic of conversation when they compare their current age with that at past viewings. In this entire substrand conversation (EthanGamer, 2020, February 17) participants clearly seek commonality by deploying colloquial expressions of agreement, in particular ‘Same’, in relation to participants’ long-standing participation in this gamer’s videos. Age is one element which is made relevant by participants as a component of interaction to establish commonality and promote affiliation, with ‘naming’ a commonly used interactional device to promote understanding.

Example 6.5 provides further evidence of how young users promote affiliation by recounting past experiences with Ethan Gamer’s channels in EthanGamer (2020, February 17), the extended substrand, which may lead to talk about age and the passing of time.

User B’s rather long post in Example 6.5, comprises a ‘telling’ or story about a past event, which contributes to the nostalgic tone of this substrand. This telling conforms to Schegloff’s (2007) definition of an announcement which is considered ‘a telling packaged in a single, grammatically simple, turn-constructional unit’ (p. 42). Tellings have also been identified in Facebook (Farina, Reference Farina2015) and can lead to a second telling in response. The reminiscing which occurs in this substrand leads to users sometimes talking about their age. After User B’s telling on an occasion where he got into trouble for watching Ethan Gamer, he provides a positive assessment of the channel (‘still love this channel’), though he appears to prefer the previous young voice of the star (‘but miss his young voice :()’, a comment which is reinforced by the sad emoticon. Users C and D’s comments (‘Same’) in posts 3 and 4 express agreement with one or more components of User B’s post while User E responds with another brief second telling regarding his last past viewing of Ethan Gamer’s videos. No profile pictures are available in Examples 6.2 to 6.5 to indicate age or gender of participants, as users choose initials in these cases.

As noted in the analysis so far, time and age is frequently made relevant by users in both the I Have a Big Belly (EthanGamer, 2020, February 17) and Baby Cow Processor (EthanGamer, 2015, February 20) main strands and substrands. Related to these concerns, it is common for users to introduce a nostalgic element. They frequently do this by announcing their return to Ethan Gamer YouTube videos after a break or by recounting their past positive experiences, as we observed in the first posts in Examples 6.4 and 6.5.

In summary, the fact that participants appear to be using adults’ accounts is evident when children reveal their young age in YouTube substrand talk, which contrasts with profile names and pictures. Talk about age is especially evident in participants’ comparisons of one anothers’ age to establish commonality and in tellings, where they share previous experiences related to viewing of Ethan Gamer gaming videos at various ages. This contributes to the nostalgic element of the conversations, including EthanGamer (2020, February 17). This extended substrand is mostly dedicated to connecting and agreeing with other users regarding their return to Ethan Gamer TV after a break, though brief tellings from the past are also a feature of this environment within longer posts.

Achieving Understanding Where Recipiency Is Disrupted

This section focuses on the Baby Cow Processor comments initially (EthanGamer, 2015, February 20) and then considers the extended substrand (EthanGamer, 2020, February 17) for comparison. In EthanGamer (2015, February 20), there are a total of sixty-five substrands, elicited by single main strand comments. Of these, sixteen were self-posts or posts that main strand commenters posted to themselves. This leaves a total of forty-nine collaborative substrands where main strand posts prompted responses from other users.

Linguistic Evidence of Children’s Developing Literacy

Developing literacy is evident in the non-standard language commenters use. While even adult chat language is generally non-standard and informal in written online conversation, with plenty of spelling errors and other irregularities due to the need for speedy typing of posts, commenters in the data regularly display language which typifies children’s developing literacy. Specifically, it is common for chat participants, adult or child, to misspell words and use non-standard language in online interaction on social media, in part because this is a unique form of informal written conversation. This requires participants to adapt their ‘talk’ to a written environment when posting their contributions. Where online written interaction occurs in real time, they often need to write and post their contributions under time pressures. In any case, unconventional spelling and vocabulary is generally considered acceptable in this context.

Given the likely prevalence of child participants in YouTube comments interaction examined in this text, their language tends to reflect their developing written language and literacy. For example, as the reader may have noticed in some examples presented thus far, they tend to write as they speak and may at times confuse the spelling of words (homophones) that sound the same but have a different meaning, such as ‘their’, ‘they’re’ and ‘there’ or ‘two’, ‘too’ and ‘to’. This is because they are still becoming accustomed to rules related to correspondence between phonemes, the smallest units of speech, and graphemes, the smallest units of writing (letters or groups of letters). This is also the case where grammatical irregularities are evident. There are multiple instances of non-standard spelling and grammar in the data and sometimes ‘invented’ spelling (Gleason Berko & Ratner Bernstein, Reference Gleason Berko and Bernstein Ratner2009, p. 418), which is common to children. The following examples provide evidence of a variety of non-standard items which might be considered typical of the developing language of children, though some may be typographical errors. They may also be present in adult writing.

In Example 6.13, also reproduced in Example 6.11 above, User A uses ‘grew’ instead of ‘grown’ in a positive but nostalgic assessment of Ethan Gamer.

While ‘u’ is an accepted abbreviation of ‘you’ in social media interaction, the use of past tense verb ‘grew’ instead of past participle ‘grown’ with ‘have’ indicates developing knowledge of English verb use which is less likely to occur in adult language.

The misspelling of ‘processor’ in ‘cow proseser’ in Example 6.14 is another example of young users’ developing language and literacy which is visible in the data.

Despite the fact that the YouTube video being referred to is entitled Baby Cow Processor, with the title visible on the landing site, this user does not reproduce ‘Processor’ exactly and contributes his own version by mapping the sound to the written word.

A similar solution to writing the sound corresponding to ‘videos’ occurs in Example 6.15.

In the main strand comment (post 1), the user posts his own invented version of ‘videos’, that is, ‘fidiows’ which is nonetheless likely to be comprehended by other users. In this example, it is relevant that User A appears to sign using his real name, which is masculine, beneath the main post. This allows him to distinguish himself from the profile name, which is feminine. This also suggests that User A may be a child rather than an adult.

In Example 6.16, the star’s name is spelt as ‘Ethen’ rather than Ethan.

While this could be a typographical rather than spelling issue, as with other spellings noted thus far, this rendition of ‘Ethan’, with an ‘e’ in place of ‘a’, may occur because writers do not distinguish how certain sounds in English are realized in written form if they sound the same, as in this case. We saw a similar case in the ‘Who’s waching’ sequence (Example 6.10), where the ‘t’ in ‘watching’ is dropped by a user without any social consequences in the comments.

Homophones such as ‘to’, ‘too’ and ‘two’ sound the same and children (and often adults) confuse them in their written form, as in Example 6.17.

In this case User C’s ‘me to’ rather than ‘me too’ in post 3 is an affiliative response to User A’s emotional expression of endearment towards Ethan Gamer. This post expresses agreement and suggests she feels the same way about Ethan Gamer as User A.

In Example 6.18, User A receives a response to his main comment from Ethan Gamer in the more private substrand.

Ethan Gamer’s ‘TYSM’ (thank you so much), an expression of appreciation, responds to User A’s positive assessment in post 1. User A then responds with an appropriate second pair part to complete the ‘thank you’ routine with ‘your welcome’ where she does not appear to distinguish the pronoun ‘your’ from the verb phrase ‘you’re’.

To summarize, there is evidence that children use non-standard spellings in their language to express themselves on YouTube comments, as is likely to occur in written interaction on other social media or in traditional offline writing where English is used. These spellings may be due to their developing ability to match spoken with written renditions of English words, so they may write words that sound the same but are written differently. Hence, their spelling reflects how these words are spoken phonetically. What is interesting about the various linguistic irregularities which abound in the data is that there is little evidence of other users repairing this language in the more private substrands where this would be less face-threatening. This is most likely due to the general tolerance towards the unique language of chat and non-standard versions of written language. Any instances of other-repair are in fact more likely to relate to errors of fact than language. For example, we earlier discussed examples where users correct one another in relation to gaming hardware used by Ethan Gamer (Examples 6.6 to 6.8), which are worth considering in the next section on other-repair.

Other-Repair Sequences

This section explores how children deploy conversational repair in the constrained YouTube comments context. Evidence so far in fact suggests that other-repair or correction is more likely to concern errors of fact related to technical issues rather than of linguistic expression (see Examples 6.3, 6.6 and 6.7). This section also considers whether repair as an interactional resource is likely to lead to learning in the substrands, given its potential role as a scaffold.

Example 6.19 is an extract from previously discussed Example 6.7, where repair was not considered. In this case, the repair is related to gaming hardware used by Ethan.

User D interprets User A’s question ‘do u have Xbox 360’ as being directed to Ethan Gamer, because he uses the pronoun ‘he’ rather than ‘I’ in his response to User A. His negative response ‘No’ in post 4 initiates a repair and indicates there is a problem with User A’s suggestion. In the same post he also corrects (other repairs) the suggestion that Ethan Gamer is using an Xbox 360, by providing information on what he considers the correct alternate, that is, the correct gaming hardware, a PlayStation (‘ps’). So there are two components, a negative response and justification for that response (attendant activity), which constitute the repair post.

In Example 6.20, there is a similar repair of fact related to gaming hardware.

In Example 6.20, User A assumes that Ethan Gamer is using an Xbox in her main strand question and seeks clarification on which particular version he is using. She addresses Ethan Gamer directly and in the same post she expresses strong endearment towards him both verbally and by deploying nine couple emojis with a heart, which suggests a relationship. User B1, a regular contributor to this substrand intervenes with a correction (other-repair) since Ethan Gamer apparently uses a PS3 rather than an Xbox. No further interaction occurs between these participants in the substrand; however, it seems that User B1 in this instance has used the substrand, a more private environment than the main strand, to complete his correction and assist User A in understanding the gameplay.

Other instances of other repair may relate to language though these are uncommon in the data. In Example 6.21, one user, a regular contributor, plays with language and produces a pun in the repair format.

User A1 uses a question format to request that Ethan Gamer make an elephant in Minecraft, assuming that he will respond and that his gameplay is occurring in real time, which is not necessarily the case. He receives a response from User B, who begins his contribution as a correction ‘You mean’ and concludes with a mock linguistic correction of ‘elephant’, suggesting ‘Ethanphant’ instead, playing on the word ‘elephant’ to include Ethan Gamer’s first name. User B signals the playful nature of the repair by including a big smile emoticon ‘:D’ followed by verbal clarification that her statement is in jest ‘PUN INTENDED’ in capital letters for emphasis. Hence, this is not a true repair despite its being in repair format linguistically and suggests that users may occasionally engage in linguistic play in this environment.

Linguistic play also occurs in Example 6.22, which includes an other-repair related to language of the Minecraft game.

Example 6.22 includes two repairs. One may in a sense be considered an indirect repair of Ethan Gamer’s language in post 1 because it addresses other users while referring to the star’s talk using a third person pronoun (‘he said’). The subsequent repair by User B (‘+ User A it’s mooshroom’) in post 2 on the other hand is a direct repair of the main strand post by User A, who uses ‘mushroom’ in place of the correct Minecraft descriptor ‘mooshroom’. This term denotes a mushroom-covered variant of a cow. Hence, User B’s repair consists of an explanation ‘it’s’ followed by the correct alternate ‘mooshroom’. User A is in fact named specifically with the + symbol. This correction post is reinforced with an additional explanation by User C, that a mooshroom is ‘a type of cow’. A humorous element is introduced as part of this comment, with the inclusion of a pile of dung emoji, which might be associated with a cow. Hence, this repair is linguistic but relates to the language of Minecraft which only Minecraft users would understand. User C collaborates with User B in completing the repair with a further explanation and the support of a humorous emoji to lighten up what might otherwise be perceived as a face-threatening act.

While in Example 6.22 we see participants’ efforts to use the correct language of Minecraft, Example 6.23 shows a rather anomalous repair, where an accepted term in text chat ‘u’ is corrected.

In Example 6.23, users compare Ethan Gamer with other YouTube gaming celebrities, Squiddy and DanTDM, but do not always agree. User E in fact disagrees with previous assessments that ‘sqiddy’ and ‘Dan tdm’ are not as good as Ethan Gamer, as suggested by User B and D, who agree with the positive assessments by User A in the first post. User E takes issue with User D in particular by using the + sign to name him (‘+User D’). He then expresses his strong appreciation of DanTDM, who User D appears to consider inferior to Ethan Gamer. He follows this with an expression of dislike of User D (post 5). In post 8, User G also takes issue with a prior post, addressing a user (unknown user), who is known to him with another pseudonym but which is unavailable in the comments. He then takes aim specifically at User E, for whom he expresses dislike in post 9 ‘I don’t like u’. User I follows this post with a linguistic correction, specifically of the widely accepted abbreviation of ‘you’ which is widely adopted in online communication as ‘u’. This is somewhat unusual according to previous research, as gamers and social media users tend to promote the use of language which is appropriate to online contexts. There is in fact no further conversation in the substrand after this correction, though this may be due to reasons other than the repair.

In summary, despite the existence of examples of linguistic other-repair discussed above, it is clear that linguistic repair is less frequent than errors of fact in the data, despite the fact that substrands would permit this to occur in a more private context than the main strand comments. While it is possible to engage in repair thanks to the affordances of YouTube substrand comments, in the context under examination, young YouTube commenters appear to be more preoccupied with other matters, such as understanding the video they are watching, comparing Ethan Gamer with other celebrities and connecting with other gamers with similar interests. Therefore, linguistic repair in YouTube comments is unlikely to be used as a learning tool, but rather, the preference is for repair of errors of fact to promote understanding and learning related to the video and Minecraft gameplay, in collaboration with other users. While learning is not evident in the online conversations, it is clear from participants’ efforts to scaffold other users through conversational repair, that watching the gaming video provides gamers with possibilities for learning, as stated by User A in the main strand comments.

While there is no apparent response to this statement, the use of the term ‘tutorial’ indicates that the video has a pedagogical role in relation to Minecraft gaming.

Other Forms of Collaborative Interactions

Repair is not the only interactional resource used by YouTube commenters to assist and scaffold each other. Other interactional resources which are available to users in this context, for example, questions, have been presented above. Another important resource is advice-giving, though such collaborative interactions are mostly directed at Ethan Gamer. The main strand interactions abound in such advice, as in Example 6.23, where advice posts follow each other, though they may not have been posted sequentially deliberately.

As often occurs in main strand contributions, these posts provide advice to Ethan Gamer in different ways. At the same time they fulfil other conversational actions apart from advising. Post 1 recommends that Ethan Gamer use a different mode from the one he is currently in (‘you should do peaceful’) and provides a justification for this recommendation. This may also be interpreted as a polite request, as ‘you should’ hedges this statement rather than a more peremptory command in the imperative. Post 2 instead provides an attempted pun on the verb ‘move’ with a version which includes the sound made by cows ‘MOO’ except this is in reference to sheep. The intended humour in this comment is reinforced by the big smile emoticon at the end and appears to be an attempted, mock linguistic repair of an utterance produced by Ethan Gamer in the video. Hence, the target audience of these posts is Ethan Gamer whose video is, however, not a livestream; it is prerecorded. Hence, while linguistically the target audience is Ethan Gamer, users may be aware of ‘overhearing’ audiences who are participating in the comments interaction without posting comments or perhaps limiting their responses to ‘likes’.

Example 6.26 also consists of advice-giving except that it is followed by likes and agreement in a substrand.

This gaming advice is not clearly directed at anyone in particular. The first comment ‘Ethan should Milk them to’ is in the third person and is therefore about Ethan so it is a form of indirect advice and attempt to engage with YouTube comments audiences. However, the pronoun ‘you’ is subsequently used and may either be impersonal or directed at Ethan Gamer. Hence, it is another case of unclear recipiency which is common in this environment, especially main strand comments. It does, however, provide advice in a rather lengthy post, with a series of suggestions related to the game which is available to all commenters. User B’s substrand response (‘Yup’) agrees with these suggestions but the post also receives five likes which denote approval and other commenters as recipients of the post.

An additional use of YouTube comments is for participants to seek assistance from other commenters, which promotes understanding of both Ethan’s and users’ own video gameplay. This is evident, for example, in our previous discussions on the use of questions and repair regarding gaming software. These are likely to contribute to participants’ understanding of the gaming video, thus promoting ZPD. There are, however, instances where participants may directly request assistance of other participants on a technical issue, as in Example 2.27.

In Example 2.27, User B1, who is a regular contributor in this context, responds to User A’s call for help in the substrand, but appears unable to assist. User A appears to be online on YouTube or she would not be able to post comments. However, her issue is probably related to accessing her gaming console, which suggests that participants engage in their own gaming activity concurrently with Ethan Gamer’s asynchronous gameplay as they are connected. Hence, her post is a clear request for technical assistance to which User B1 responds with a troubles telling about his own access woes. The complaining is reinforced by the concluding emoji which appears to express annoyance or frustration.

Conclusion

Based on available data from selected Ethan Gamer YouTube comments, the analysis indicates that YouTube comments interaction is a unique form of interaction with numerous affordances, which may provide children with social and learning advantages related to gaming, despite its constraints. While in Chapter 2 on emojis we observed the prevalence of positive evaluations directed at Ethan Gamer in YouTube main strand comments, in this chapter we have identified a wider range of conversational actions, with substrands used as a resource by young participants to connect with other gamers, whether known or unknown to them, and to improve their understanding both of Ethan Gamer’s videos and their own gameplay. These actions may include questions, repair, advice-giving, expressing agreement and tellings. Responses to questions, repair and advice-giving may potentially scaffold users’ understanding of Ethan Gamer’s gameplay and promote ZPD in relation to gaming. It should also be noted that the variety of conversational and linguistic functions in YouTube comments depends on the video as the YouTube video provides a framework for comments according to Boyd (Reference Boyd2014). For example, a political video is likely to provoke political commentary while gaming language and commentary related to gaming are visible in the data examined in this context.

As noted in Chapter 5, Gee and Hayes (Reference Gee, Hayes, Steinkuehler, Squire and Barab2012) see the multiple digital activities related to gameplay as affinity spaces because they support a shared passion among the participants. This is especially obvious from the extended substrand where a post elicited 104 comments and 148 likes. These comments were predominantly dedicated to expressing agreement with other users on their previous and current participation in the Ethan Gamer YouTube video, using various colloquial synonyms of ‘I agree’ (EthanGamer, 2020, February 17). The mostly affiliative actions by individual participants in the data examined allow them to establish a presence and promote participation in this public online gaming community.

The video viewing and related comments have the potential to facilitate improvements in gameplay through use of interactional resources which scaffold users on the YouTube comments platform. This is especially the case for the substrands, where the platform permits sequential conversations and creation of relevant first and second pair parts thanks to clearer interactional access to recipients compared to the main strand comments. Access to recipients is constrained in the main strand comments, which are interactionally disrupted due to content creators’ and the platform’s subsequent editing and reorganization of the comments based on various criteria. Specifically, interactional disruption is mainly due to disrupted recipiency in the main strand comments; however, it is reconstituted by users who engage in substrand comments. While some disruptions are generated by the software, content creators and YouTube moderators may also play a role in altering the appropriate presentation of adjacency pairs especially of the main strand.

All comments may address either Ethan Gamer, other users or an invisible audience constituted by reader-viewer recipients. According to Chau (Reference Chau2011), many users are on the periphery as non-interactional viewers, who do not use either likes, dislikes or comments. Hence, while linguistically the target audience is Ethan Gamer and other interactional users, participants who post comments are possibly aware of ‘overhearing’ audiences who engage non-interactionally in the comments interaction and may benefit from their advice, humour and general online conversation.

Analysis indicates that age is a recurrent topic in YouTube comments as participants often connect to YouTube comments using adults’ accounts. Use of an adult’s account may have the advantage of promoting safety, as adults are able to monitor their children’s online activities for safety reasons if they wish. However, this requires children to complete additional conversational work to reveal their real age and name, often using gamer tags, to other users for the purpose of interaction and gaming. This is necessary for children to participate in a support network and informal community of practice related to gaming on Minecraft and other gaming platforms. Their interactional efforts are therefore both social and learning related. They are dedicated to connecting and reconnecting with other gamers for the purpose of asking questions and seeking technical assistance in understanding the games played by content creators and possibly applying new learnings from the video to their own play.

Repair, especially other repair or correction, is an important activity afforded by the YouTube substrand environment; however, it regards mainly errors of fact, especially related to gaming hardware used by Ethan Gamer. Users are generally tolerant of non-standard linguistic features which may be due either to children’s developing literacy, accepted conventions of chat language and typographical errors. This tolerance may be due to users’ polite avoidance of face-threatening actions or their predominant interest in gaming rather than language. Gaming platforms are in fact often made relevant by users in these interactions, where differences and commonalities are established between users. Playful repairs and direct requests for help are also present, which highlight other affordances of YouTube comments for participation in social activities and gaming.

Interactions by individual users are usually brief and mostly limited to one post each in the same substrand, though some may intervene again with additional posts at various points in conversations. While there is potential for learning, this environment’s affordances are therefore limited to promotion rather than enactment of learning. Its affordances for social connectivity are however clear, though participants need to use various interactional resources, such as naming addressed participants and use of the substrands to overcome constraints related to recipiency and sequence organization, which impact on understanding of the conversations. As far as the extended substrand is concerned (EthanGamer, 2020, February 17), the interaction was predominantly social as it was dedicated to affiliative conversational work between users. It features likes and repetitive expressions of agreement, with the first post based on users’ common experience of returning to an Ethan Gamer channel after a break. It was, therefore, less varied linguistically than the briefer substrands of EthanGamer (2015, February 20).

In Summary

• Age is a relevant concern for participants in interaction due to the need to reveal their true age when using adults’ accounts, to facilitate connection with other young gamers.

• An age-related tendency by participants is to recount past experiences (tellings) on their previous engagement with Ethan Gamer YouTube videos, as part of a search for commonality with other participants.

• YouTube comments users may sometimes use a question format to seek out participants from the current year, to connect with other gamers based on a common time of participation (temporal copresence).

• All YouTube comments interaction is asynchronous, sometimes with significant differences in time of contribution.

• Substrand posts can only be elicited by a mainstrand post, which constitutes an initial first pair part to which substrand posts mostly respond, as second pair parts of adjacency pairs. Additional first and second pair parts may however sometimes be created when new conversational sequences are created between substrand participants other than the first poster.

• Main strand comments interaction is not usually sequential, even when the ‘newest first’ option is selected; hence, only the more private substrand comments are likely to permit coherent interaction.

• Likes or ‘thumbs up’ may be seen as a form of second pair part which is posted in response to a main strand comment, to form an adjacency pair.

• Recipients of substrand and main strand comments are not always clear unless they are named by users. This may cause interactional confusion and disrupted adjacency pairs and recipiency, though most posts are intended for either Ethan Gamer, users in general or specific users if named. Naming is thus an important interactional device which promotes understanding in YouTube comments multi-party interaction.

• While linguistically the target audience is Ethan Gamer and other interactional users, active users are probably aware of ‘overhearing’ non-interactional reader-viewer recipients.

• There is often a correspondence between number of likes and length of substrands elicited by a main strand comment.

• Questions quite often elicit substrand responses, which suggests this is a linguistic format that projects answers even in the YouTube comments environment.

• YouTube commenters use this forum to connect with both unknown and familiar users.

• YouTube users engage in technical talk, to better understand Ethan Gamer’s gameplay and to apply new knowledge derived from the video to their own gaming efforts. This talk also allows them to connect with users with similar hardware for possible gaming outside the YouTube space.

• Children’s non-standard spellings in their language on YouTube comments may in some cases be due to their developing ability to match spoken with written renditions of words. Repair of such language rarely occurs, given social media users’ general tolerance towards non-standard renditions of written language and the unique language of chat.

• The rare instances of other-repair which occur in YouTube substrand interaction are more likely to relate to errors of fact than language; they are sometimes completed collaboratively and accompanied by emojis or emoticons that mitigate the possibly face-threatening nature of repair.

• While other-repair is clearly an affordance of YouTube comments substrand interaction, it is not commonly used. The data indicates that users are more preoccupied with understanding the video and game they are watching, comparing Ethan Gamer with other celebrities and connecting with other gamers with similar interests and gaming platforms.

• Linguistic play, especially puns, is one creative feature of YouTube substrand interaction which is usually related to the gaming context, in this case Minecraft gaming.