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In Just Like Us: Digital Debates on Feminism and Fame, Caitlin E. Lawson examines the rise of celebrity feminism, its intersections with digital culture, and its complicated relationships with race, sexuality, capitalism, and misogyny. Through in-depth analyses of debates across social media and news platforms, Lawson maps the processes by which celebrity culture, digital platforms, and feminism transform one another. As she analyzes celebrity-centered stories ranging from \"The Fappening\" and the digital attack on actress Leslie Jones to stars' activism in response to #MeToo, Lawson demonstrates how celebrity culture functions as a hypervisible space in which networked publics confront white feminism, assert the value of productive anger in feminist politics, and seek remedies for women's vulnerabilities in digital spaces and beyond. Just Like Us asserts that, together, celebrity culture and digital platforms form a crucial discursive arena where postfeminist logics are unsettled, opening up more public, collective modes of holding individuals and groups accountable for their actions.

The abundance of information on social media has reshaped public discussions, shifting attention to the mechanisms that drive online discourse. This study analyzes large-scale Twitter (now X) data from three global debates—Climate Change, COVID-19, and the Russo-Ukrainian War—to investigate the structural dynamics of engagement. Our findings reveal that discussions are not primarily shaped by specific categories of actors, such as media or activists, but by shared ideological alignment. Users consistently form polarized communities, where their ideological stance in one debate predicts their positions in others. This polarization transcends individual topics, reflecting a broader pattern of ideological divides. Furthermore, the influence of individual actors within these communities appears secondary to the reinforcing effects of selective exposure and shared narratives. Overall, our results underscore that ideological alignment, rather than actor prominence, plays a central role in structuring online discourse and shaping the spread of information in polarized environments.

\"This book explores the key concepts of data mining and utilizing them on online social media platforms, offering valuable insight into data mining approaches for big data and sentiment analysis in online social media and covering many important security and other aspects and current trends\"-- Provided by publisher.

Gangstalking is a novel persecutory belief system whereby those affected believe they are being followed, stalked, and harassed by a large number of people, often numbering in the thousands. The harassment is experienced as an accretion of innumerable individually benign acts such as people clearing their throat, muttering under their breath, or giving dirty looks as they pass on the street. Individuals affected by this belief system congregate in online fora to seek support, share experiences, and interact with other like-minded individuals. Such people identify themselves as targeted individuals. The objective of the study was to characterize the linguistic and rhetorical practices used by contributors to the gangstalking forum to construct, develop, and contest the gangstalking belief system. This mixed methods study employed corpus linguistics, which involves using computational techniques to examine recurring linguistic patterns in large, digitized bodies of authentic language data. Discourse analysis is an approach to text analysis which focuses on the ways in which linguistic choices made by text creators contribute to particular functions and representations. We assembled a 225,000-word corpus of postings on a gangstalking support forum. We analyzed these data using keyword analysis, collocation analysis, and manual examination of concordances to identify discursive and rhetorical practices among self-identified targeted individuals. The gangstalking forum served as a site of discursive contest between 2 opposing worldviews. One is that gangstalking is a widespread, insidious, and centrally coordinated system of persecution employing community members, figures of authority, and state actors. This was the dominant discourse in the study corpus. The opposing view is a medicalized discourse supporting gangstalking as a form of mental disorder. Contributors used linguistic practices such as presupposition, nominalization, and the use of specialized jargon to construct gangstalking as real and external to the individual affected. Although contributors generally rejected the notion that they were affected by mental disorder, in some instances, they did label others in the forum as impacted/affected by mental illness if their accounts if their accounts were deemed to be too extreme or bizarre. Those affected demonstrated a concern with accumulating evidence to prove their position to incredulous others. The study found that contributors to the study corpus accomplished a number of tasks. They used linguistic practices to co-construct an internally coherent and systematized persecutory belief system. They advanced a position that gangstalking is real and contested the medicalizing discourse that gangstalking is a form of mental disorder. They supported one another by sharing similar experiences and providing encouragement and advice. Finally, they commiserated over the challenges of proving the existence of gangstalking.

How does social media content affect users’ online discourse? Existing scholarship sheds light on how several social media features involving content can influence users’ speech. However, this research often conflates content’s lexical dimension with its symbolic dimension. The authors analyze how the symbolic properties of online content can distinctly affect discourse on social media. Specifically, they examine how the symbolic meanings conveyed by Twitter’s reinstatement of Donald Trump’s account influenced Twitter users’ discourse. The results of embedding regressions indicate that Trump’s reinstatement immediately shifted users’ discourse about social and political identity-based groups, but only when they discussed Black and Jewish people. Additional results suggest that the discourse became more politicized and that the discursive shift was short lived. The authors’ findings contribute conceptual and analytical clarity to the sociosemantic dynamics of online discourse, encouraging future research to distinguish and compare the lexical and symbolic dimensions of online content.

In many instances, tourism has begun to be perceived by touristic cities' residents as an important problem. We examine the phenomenon of antitourism and, in particular, the discourses of rejection and resistance against tourism in the city of Barcelona. Previous research has examined residents' attitudes and behaviors towards tourism development from both a cognitive and emotional aspect, but we still lack a more qualitative, in-depth understanding of residents' emotion discourses. Furthermore, for this research, a novel type of dataset has been analyzed-that is, discourses constructed in online media. In particular, the study was based on the analysis of the comment threads of news articles about the touristic impact on Barcelona. In total, 6,916 comments posted in online news articles were examined. This analysis also permitted to observe the interaction between two different actors, the media and the residents, and to see how residents respond to the media's framings about tourism in Barcelona.

Biafra secessionist agitations in Nigeria continue to generate varied conversations online and offline. This study applies critical discourse analysis and the appraisal framework in examining social actor representations in the ongoing Biafra agitations in Nigeria. It analyses posts produced by interlocutors, as they express variegated stances towards the agitations and its actors, within two vibrant Nigerian digital communities, Nairaland and Nigeria Village Square. This study identifies binary social actor positioning, revealing both negative valence and positive self-representation strategies towards the agitations and principal social actors in the agitations. Expressed within the appraisal resources of attitude, engagement and graduation, these valuations result in the distribution of socially and emotionally constructed identities for the principal social actors in the agitations. Such distribution is socio-cognitive, as there is the likelihood that the representations might evolve into the creation of new ideological orientations or the reinforcement of existing ideological leanings, whose consequences are potentially double-edged for tranquillity in the Nigerian polity.

When we encounter toxic comments online, how might individual efforts to reply to those comments improve others’ experiences conversing in that forum? Is it more helpful for others to publicly, but benevolently (with a polite tone, demonstrated understanding of the original comment, and empathy for the commenter; Young Reusser et al., 2021), correct the post? Is going along with or joking along with the commenter in a benevolent way helpful? Or is retaliating – returning toxicity for toxicity – the best strategy? Using real Reddit conversation pairs – a toxic comment followed by a reply – as stimuli, we conducted a pilot study (n = 126 participants) and pre-registered experiment (n = 1357 participants) investigating the impact of three kinds of replies to online toxicity (benevolent correction, benevolent going-along, or retaliation) on observers’ self-reported freedom to contribute to the conversation, their belief that the toxicity will be reduced, and their overall impression that justice has been restored. We found evidence that benevolently correcting the toxicity helped participants feel freer to contribute than retaliating against it. Benevolently correcting was also seen as the best option for dissuading the toxicity and restoring justice. These findings suggest that treating toxic commenters with empathy, understanding, and politeness while correcting their toxicity can be a useful strategy for online bystanders who want to intervene to improve the health of online discourse. Preregistered Stage 1 protocol: https://osf.io/hfjnb (date of in-principle acceptance: 01/23/2023).