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Centering on social media’s public- and profit-oriented nature, this study theorizes how social media users are empowered and constrained when participating in platform governance through user-initiated expressions on platforms. The empirical analysis focuses on user responses before and after Elon Musk’s official acquisition of Twitter, utilizing cluster analysis and topic modeling to examine the volume and content of related discourses among different Twitter user groups. Our results point to user constraint in platform governance. Although a diverse set of users, such as partisans, bots, and cryptocurrency enthusiasts, spoke up, they had diverging and sometimes conflicting objectives; and partisans dominated the conversations. There was an upsurge in user volume and activity level post-acquisition among liberal users, whose critical voices on platform governance might have bolstered platform business. Potential bots also increased in volume and amplified political topics. Our findings shed light on the challenges of user-driven platform governance, underscoring the complex interplay between platform users, economy, and governance.

This study investigated portrayals of women in STEM on TikTok focusing on their self-presentation of identity and use of platform features to promote audience engagement. This quantitative content analysis examined TikTok posts ( N = 400) from a 3-month sample of 100 TikTok accounts by individuals identified as women in STEM. Results for STEM-focused posts showed that these content creators provided positive portrayals of their work as women in STEM and frequent displays of their STEM identity, particularly displays of STEM competence and self-recognition. However, findings also indicated that this TikTok community displayed other social group identities less frequently and used relatively few TikTok platform features that would likely enhance audience engagement. Results suggest that positive portrayals of women in STEM on TikTok are helpful for challenging gender-STEM stereotypes, but the dearth of displays of social group identities highlights a need for more diverse women in STEM role models on TikTok. In addition, the infrequent use of popular platform features appears to be a missed opportunity for broader audience engagement. Implications for social media science influencers, science communicators, and informal STEM outreach professionals are discussed.

BIPOC scholars have criticized that feminism and feminist activism have often failed to include race, class, and intersectional identities in the feminist agenda. Using theoretical concepts from framing, rhetoric, and cross-platform activism, we examine (a) the discourse in social media posts around white feminism and (b) the platform differences of this content across five different social media platforms: Twitter, Facebook, Instagram, Reddit, and YouTube. The methodology we use is a combination of computational text analysis approaches and content analysis. Our study highlights the voice of those who felt marginalized by the feminist movement including the uprising of #MeToo. We find pockets of conversations on topics such as experiences of People of Color or Women of Color; critique of white feminism, experiences of LGBTQ+ communities, and Black experiences. These posts predominantly used techniques to persuade the audience with reason, facts, and logic. The most common framing technique used was acknowledgment. Moreover, our findings show multiple differences across the five social media platforms.

The recent rise of political extremity and radicalization has presented unique challenges to contemporary politics, governance, and social cohesion in many societies in the world. In this study, we propose an imagined audience approach to understand how social media’s expanded expression capabilities are related to users’ political extremity and reduced network interaction. We demonstrate the usefulness of our imagined audience framework using a multi-country survey data set. Results from the United States, South Korea, and Japan reveal that expressive use of social media is associated with more extreme political attitudes and heightened intolerance, but the effect is contingent on whom the expresser has in mind as their audience. In particular, expressing one’s political self has a depolarizing effect for those expecting low audience reinforcement. We test the boundary conditions of our model in a more restricted information environment with a Chinese sample. We conclude by discussing the significance of our imagined audience approach and its relevance to today’s technology-mediated self-presentation.

This study explores the framing strategies and language features of U.S. news coverage surrounding sexual violence and gender issues across the ideological media spectrum at two pivotal phases of the #MeToo movement: (1) during its initial rise as a hashtag-driven social movement in 2017 and (2) during the Kavanaugh nomination and confirmation in 2018. Using structural topic modeling, community detection, and feature extraction, we reveal a heightened employment of political framing during the Kavanaugh accusations. Topical prevalence and language use in news treatment also showed clear partisan differences, consistent with theories of moral foundation and issue ownership. Implications for research on news coverage of gender rights and framing of social movements are discussed. [ABSTRACT FROM AUTHOR]

Guided by the integrative theory of communication work, we present a computational and qualitative analysis of Reddit comments authored by patient-users living with chronic overlapping pain conditions. We first employed computational text analysis to compress the data corpus via structural topic modeling. The community detection algorithm Louvain was employed to identify communities of topics within the data. Then, we extracted a subset of the data and performed a computer-aided qualitative thematic co-occurrence analysis. Topic modeling revealed 35 topics and five thematic communities. The qualitative analysis revealed that these topics mapped onto and extended the typology of communication work and contributing factors and identified co-occurrence patterns both among and across research questions. Our findings offer methodological, theoretical, and practical implications. [ABSTRACT FROM AUTHOR]

BIPOC scholars have criticized that feminism and feminist activism have often failed to include race, class, and intersectional identities in the feminist agenda. Using theoretical concepts from framing, rhetoric, and cross-platform activism, we examine (a) the discourse in social media posts around white feminism and (b) the platform differences of this content across five different social media platforms: Twitter, Facebook, Instagram, Reddit, and YouTube. The methodology we use is a combination of computational text analysis approaches and content analysis. Our study highlights the voice of those who felt marginalized by the feminist movement including the uprising of #MeToo. We find pockets of conversations on topics such as experiences of People of Color or Women of Color; critique of white feminism, experiences of LGBTQ+ communities, and Black experiences. These posts predominantly used techniques to persuade the audience with reason, facts, and logic. The most common framing technique used was acknowledgment. Moreover, our findings show multiple differences across the five social media platforms. [ABSTRACT FROM AUTHOR]