How does the language of male and female politicians differ when they communicate directly with the public on social media? Do citizens address them differently? We apply Lasso logistic regression models to identify the linguistic features that most differentiate the language used by or addressed to male and female Spanish politicians. Male politicians use more words related to politics, sports, ideology and infrastructure, while female politicians talk about gender and social affairs. The choice of emojis varies greatly across genders. In a novel analysis of tweets written by citizens, we find evidence of gender‐specific insults, and note that mentions of physical appearance and infantilising words are disproportionately found in text addressed to female politicians. The results suggest that politicians conform to gender stereotypes online and reveal ways in which citizens treat politicians differently depending on their gender.

This paper explores Twitter adoption and social media engagement of private German environmental foundations. The study follows Lovejoy and Saxton’s (2012) approach to the hierarchy of social media engagement. It demonstrates the domination of an information provision role on Twitter and the almost equal relevance of action mobilizations and community building posts. At the same time, the study supplements the existing typology with the additional dimension of communication partners addressed in each type of tweet. Finally, using data from interviews, the study interprets and explains the role of social media tweets and patterns of engagement with different groups. In-depth analysis of tweets and interviews with the foundation representatives confirmed a limited use of social media as a means for dialogue and community development. Simultaneously, analysis shows that tweets posted by foundations predominantly address a professional community of other civil society actors, experts and politicians, creating an online expert bubble. Interviews confirmed that such online connections mirror offline cooperation networks that are perceived to be more important for successful communication and project development by the investigated organizations.

This article illustrates how qualitative and network evidence complement one another for obtaining a deeper understanding of meso-level social orders theorized as strategic action fields. Making use of network data based on Twitter follower relationships and building on a previous qualitative study on the food charities active in Greater Manchester, we show how network-analytic formalizations of even apparently unimportant digital connections—Twitter ‘follows’—can provide meaningful insights into the functioning of strategic action fields. Focusing on this local charitable food provision field, the article makes a number of broader empirical and methodological contributions potentially relevant to the study of non-profits and other multi-organizational fields. The results of the network analyses mostly confirm the findings obtained using qualitative data, but also point to potential contradictions and puzzles that may indicate further lines of inquiry. In the discussion, we highlight the strengths and limitations of this approach and suggest how researchers could use easily available digital network data at different phases of their field investigations.

The quantitative data sources for NGO scholars are increasing, introducing new possibilities for our understanding of the global NGO population. The most frequently used data sources tend to privilege larger NGOs located in more politically open countries. We highlight two developments. First, we introduce a new Global Nonprofit Registry of Data Sources (GRNDS) dataset. GRNDS documents the information that governments collect and release to reveal variations in the data environment. Second, new sources of information from social media and donation platforms avoid the filtering and curation of reports from nonprofit regulators. These include Twitter, Google Trends, and new data from #GivingTuesday. Together, this richer information on cross-national variation in reporting and quickly available digital data should help research build a richer picture of the global NGO sector.

We examine Twitter data to assess the impact of media exposes on the reputations of two international nonprofits, Oxfam and Save the Children (STC). Using a random sample of 6794 Tweets, we study the daily gap between positive and negative sentiments expressed towards these organizations. The “unweighted gap” and the “weighted gap” (weighted by the number of followers) of the Twitter handle follow broadly the same trajectory with high fluctuation in response to new negative or positive media stories. Twitter handles with large audiences amplify variability in weighted gap. While Oxfam’s reputation did not fully recover to pre-Haiti levels even 6 months after the scandal, STC’s reputation returned to pre-scandal levels in 8 days, although it fluctuated in response to new revelations. Overall, reputation recovery for both organizations was aided when they received celebrity endorsements and focused public attention on their positive activities, especially by linking to visible global events.

Altmetrics are an emerging form of bibliometric measurement that capture the online dimension of scholarly exchange. Against the backdrop of both a higher education landscape increasingly focused on quantifying research productivity and impact, as well as literature emphasising the need to address gender bias in the discipline, we consider whether and how altmetrics (re)produce gendered dynamics in political science. Using a novel dataset on the Altmetric Attention Scores (AAS) of political science research, we investigate two questions: Do AAS vary by gender? And how do AAS relate to gendered social media dynamics? We find that AAS reproduce gendered dynamics found in disciplinary publication and citation practices. For example, journal articles authored exclusively by female scholars score 27% lower on average than exclusively male-authored outputs. However, men are also more likely to write articles with an AAS of zero. These patterns are shaped by the presence of high-scoring male “superstars” whose research attracts much online attention. Complementing existing scholarship, we show that the AAS closely overlaps with virality dynamics on Twitter. We suggest that these gendered dynamics may be hidden behind the seemingly neutral, technical character of altmetrics, which is worrisome where they are used to evaluate scholarship.

What explains Members of European Parliament's (MEPs’) decisions to recognize some interest groups as relevant policy actors? Addressing this question is fundamental for understanding the role of political elites in shaping patterns of interest representation and interest groups’ role in legislative decision making. Building on theories of legislative behaviour and informational theories of legislative lobbying, we argue that MEPs give recognition to those organizations that are instrumental for achieving key political goals: re‐election, career‐progression and policy influence. The pursuit of these goals generates different patterns of MEP recognition of interest groups. We contribute to the literature in three ways. Conceptually, we propose interest group recognition as a key concept for understanding interactions and links between legislative and non‐legislative actors. We illustrate the high conceptual relevance of recognition for interest groups research while noting its conspicuous neglect in the literature. We address this gap and place the concept central stage in understanding legislators’ attention to and behaviour towards interest organizations. Theoretically, we build on a classic framework explaining legislators’ behaviour and refine it through the lenses of informational theories of legislative lobbying. We argue and show that legislators recognize organizations that enhance electoral prospects in their home Member States, and that legislator–group ideological proximity and an interest group's prominence in a specific policy field affect MEPs’ decisions to recognize some organizations as relevant actors. Our argument acknowledges the importance of the broader context in which MEPs operate and pays attention to how they react to and interact with it. Empirically, we propose an original and innovative research design to identify and measure recognition with the help of social media data. Our measurement strategy constitutes a significant improvement insofar that it reduces the challenges of measurement bias usually associated with self‐reported data generated through interviews, surveys, or the textual analysis of newspaper articles and official documents. Our research design allows using fine‐grained measures of key dependent and explanatory variables and offers the very first analysis of MEP interest group recognition that holds across decision‐making events and policy areas. We test our argument on a new dataset with 4 million observations recording the recognition of more than 7,000 organizations by 80 per cent of MEPs serving in EP8. We find that MEPs are more likely to recognize organizations from their Member State, particularly under flexible‐ and open‐list electoral institutions. MEPs are also more likely to recognize organizations that share their ideological affinities and are prominent actors in policy areas legislators specialize in.

How might donor influence shape the ways community foundations engage with public constituents? Using donor-advised funds to proxy for donor influence, I combined content analysis and structural topic modeling to analyze the themes of 4,055 public engagement messages sent by community foundations on Twitter. The structural topic model results revealed that donor influence significantly varied the themes of public engagement tweets. Strong donor influence was significantly correlated with greater use of policy advocacy and public education messages but negatively correlated with public mobilization and dialogic messages. This study contributes to a growing line of research on donor control and provides important insights into the power dynamics among the triad of community constituents, donors, and foundations.

Social media are the great social leveler – or so some commentators would have us believe. Social media put the power of communication directly into the average person’s hands. They also present opportunities for politicians to improve their contacts with the common person – to directly share their messages with and better understand the concerns of constituents. This study explores whether and to what extent the potential for such citizen–politician engagement is fulfilled. Deploying an original dataset of tweets from politicians in the Netherlands, the United Kingdom, and the United States, this exploratory study examines the interlocutors with whom politicians engage reciprocally via Twitter. The results show that a large share of politicians’ genuinely reciprocal exchanges includes average citizens. Although there is much room for improvement, this study suggests that Twitter is indeed opening spaces for citizens and policymakers to engage one another on matters of political import.

Which Canadian Members of Parliament (MPs) are on Bluesky and what types of content do they share? Taking up calls for more mere description of how emerging social media platforms are used in their initial period of operation, this research note describes how many MPs are using Bluesky and what types of content they share. Of the 123 MPs already on Bluesky, we find that they apply the same logic and understanding of platform affordances from Twitter (now X), with posts most frequently discussing policy, the Ottawa bubble and their constituency. This research note contributes to our understanding of how MPs use Bluesky to communicate with the public in a high-choice media environment.

There are two main ways Russian propaganda reaches Japan: (a) the social media accounts of official institutions, such as the Russian Embassy, or Russian state-linked media outlets, such as Sputnik, and (b) pro-Russian Japanese political actors who willingly (or unwillingly) spread disinformation and display a clear pro-Kremlin bias. These actors justify the Russian invasion of Ukraine and repeat the Russian view of the war with various objectives in mind, primarily serving their own interests. By utilizing corpus analysis and qualitative examination of social media data, this article explores how Russian propaganda and a pro-Russian stance are effectively connected with and incorporated into the discursive strategies of political actors of the Japanese Far-Right.

The reconstruction efforts following the 2011 Tōhoku earthquake and tsunami (3/11) have sparked a rediscovery of the concept of kizuna (literally, “bonds between people”). Some Japanese authors, however, are contesting and expanding on this notion as a way of coming to terms with the disaster. Through the analysis of two literary works, I argue that 3/11 literature provides a model for Japan's emotional and physical reconstruction through its resourcefulness and alternative vision of kizuna.

We apply moral foundations theory (MFT) to explore how the public conceptualizes the first eight months of the conflict between Ukraine and the Russian Federation (Russia). Our analysis includes over 1.1 million English tweets related to the conflict over the first 36 weeks. We used linguistic inquiry word count (LIWC) and a moral foundations dictionary to identify tweets’ moral components (care, fairness, loyalty, authority, and sanctity) from the United States, pre- and post-Cold War NATO countries, Ukraine, and Russia. Following an initial spike at the beginning of the conflict, tweet volume declined and stabilized by week 10. The level of moral content varied significantly across the five regions and the five moral components. Tweets from the different regions included significantly different moral foundations to conceptualize the conflict. Across all regions, tweets were dominated by loyalty content, while fairness content was infrequent. Moral content over time was relatively stable, and variations were linked to reported conflict events.

What drives changes in the thematic focus of state-linked manipulated media? We study this question in relation to a long-running Iranian state-linked manipulated media campaign that was uncovered by Twitter in 2021. Using a variety of machine learning methods, we uncover and analyze how this manipulation campaign’s topical themes changed in relation to rising Covid-19 cases in Iran. By using the topics of the tweets in a novel way, we find that increases in domestic Covid-19 cases engendered a shift in Iran’s manipulated media focus away from Covid-19 themes and toward international finance- and investment-focused themes. These findings underscore (i) the potential for state-linked manipulated media campaigns to be used for diversionary purposes and (ii) the promise of machine learning methods for detecting such behaviors.

This article explores the language of social media by analyzing a selection of linguistic features in four corpora of Swedish social media available at Språkbanken Text: Blog mix, Familjeliv, Flashback, and Twitter. Previous research describes the language of these corpora as informal, spoken-like, unedited, non-standard, and innovative. Our corpus analysis confirms the informal and spoken-like nature of social media, while also showing that these traits are unevenly distributed across the various social media corpora and that they are also present in other traditional written corpora, such as novels. Our findings also reveal that the social media corpora show traits of involved and interactional language.

While prior studies have barely explored social interaction for COVID-19 across Asia, this study highlights how people interact with each other for the COVID-19 pandemic among India, Japan, and South Korea based on social network analysis by employing NodeXL for Twitter between July 27 and July 28, 2020. This study finds that the Ministry of Health and Prime Minister of India, news media of Japan, and the president of South Korea play the most essential role in social networks in their country, respectively. Second, governmental key players play the most crucial role in South Korea, whereas they play the least role in India. Third, the Indian are interested in COVID-19 deaths, the Japanese care about the information of COVID-19 patients, and the South Korean focus on COVID-19 vaccines. Therefore, governments and disease experts should explore their social interaction based on the characteristics of social networks to release important news and information in a timely manner.