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2025 Social Media Lab – Computational Social Science Summer School – Online The 2025 Computational Social Science Summer School, hosted by the Social Media Lab at Toronto Metropolitan University, is a free online training series taking place from July 14–16, 2025. Designed for researchers, students, and analysts, the sessions introduce participants to text and network analysis using Communalytic, a no-code platform. Topics include multilingual topic modeling, civility and toxicity analysis, and social network mapping, with no programming experience required.Other Toronto Metropolitan University Activity 2025-07-14 Other Bridging Divides TMU Spring Retreat A one-day, biannual meeting for Bridging Divides researchers, affiliated researchers, and HQPs at Toronto Metropolitan University (TMU), aimed at fostering collaboration, knowledge sharing, and methodological innovation. The retreat features project showcases from the Social Media Lab, presentations from colleagues at various project stages, interactive Q&A sessions, and networking opportunities to encourage methodological refinement and interdisciplinary exchange.
Other Toronto Metropolitan University Activity 2024-04-24 Other Online toxic speech as positioning acts: Hate as discursive mechanisms for othering and belonging While digital platforms foster a sense of community and identity, they also facilitate harmful exclusionary practices. In this context, toxic and hateful speech are key mechanisms not only for harming others but also marking processes of othering and belonging. In this article, we examine the role of hateful and toxic speech in structuring processes of in- and out-group formation and maintenance by focusing on a public Colombian Telegram group. More specifically, we examine how members use toxic speech to position themselves and others in relation to narratives emerging from the group by analyzing 3221 posts with high levels of toxicity. Our analysis yields insights into the complex and paradoxical uses of antisocial behavior on social media platforms. Overall, the findings of this study deepen our understanding of the social gratifications that underlie how hate and toxic speech are used to disenfranchise individuals. Toronto Metropolitan University Publication 2025-05-27 GraphOptima: A graph layout optimization framework for visualizing large networks Toronto Metropolitan University Publication 2025-01-05 I 👍 your Hate: Emojis as Infrastructural Platform Violence on Telegram Toronto Metropolitan University Publication 2025-01-01 Digital battleground: An examination of anti-refugee discourse on Twitter against Ukrainians displaced by Russia’s invasion of Ukraine Russia’s war of aggression in Ukraine has triggered Europe’s largest refugee crisis since World War II. In this case study, we investigate the prevalence and types of anti-refugee discourse about Ukrainian refugees on Twitter. Previous studies primarily focused on public discourse and attitudes toward racialized refugees and immigrants; the Ukrainian refugee crisis is unique in that it is one of the few instances of a recent refugee crisis involving people who do not come from mostly racialized communities. Using Communalytic, a computational social science tool for studying public discourse on social media, we automatically collected and identified toxic posts mentioning Ukrainian refugees during the first year of Russia’s full-scale invasion of Ukraine. We focused on posts containing toxic language, as this is where we are most likely to find examples of anti-refugee sentiments. Based on a manual analysis of 2,045 toxic posts referencing Ukrainian refugees, the most prevalent ones were politically motivated and included partisan content (33 percent), followed by posts containing expressions countering anti-refugee narratives (20 percent). These findings highlight the escalating politicization and polarization of discussions about Ukrainian refugees both online and offline. Furthermore, 53 percent of the sample aligned with pro-Kremlin narratives against Ukraine. By exploiting anti-refugee sentiments and leveraging existing political and cultural fault lines in the West, pro-Kremlin messages on Twitter contribute to diminishing support for Ukrainian refugees, minimizing the severity of the war, and undermining international support for Ukraine. Toronto Metropolitan University Publication 2024-08-12 The lure of decentralized social media: Extending the UTAUT model for understanding users’ adoption of blockchain-based social media The study uses 31 semi-structured interviews to explore users' motivations for adopting and using blockchain-based social media (BSM) platforms. The objective of the study is twofold-to collect empirical data on early adopters of BSM and to test the applicability of the Unified Theory of Acceptance and Use of Technology (UTAUT) model for explaining why some users are choosing BSM over mainstream social media (MSM) platforms. Manual content analysis of the interviews reveals that users are initially drawn to BSM due to social influence and financial incentives, but they continue to use it mainly because of the sense of community they experience. We also find that the steep learning curve, the absence of content moderation, as well as security and privacy concerns hinder the widespread adoption of these platforms. From the theoretical side, although the UTAUT model is generally suitable for examining why individuals use BSM, we suggest integrating two additional factors into the model: financial incentives and content moderation. Toronto Metropolitan University Publication 2024-08-07 Understanding communities in an age of social media: the good, the bad, and the complicated Not only does this special issue of Information, Communication and Society bring you seven fascinating articles, it also brings together contemporary thinking about community and social media. The study of community no longer must keep to a parallel track with the study of digital media. We intertwine and integrate the two, celebrating the people who are connected in a community, by whatever means.
Toronto Metropolitan UniversityPublication 2024-03-25 Social Media and Society: Introduction to the Special Issue As a scholarly domain, social media research has come a long way since the term “social media” first appeared in the literature in the early 2000s. Since then, researchers across disciplines have been actively examining the impact of social media on society. According to Web of Science, there are currently over 19,000 academic articles that include the term “social media.” This special issue of American Behavioral Scientist adds to this rapidly growing body of social media research with a focus on exploring (1) networked influence, (2) transmission of (mis)information, and (3) online and offline, which points to an unstated struggle between top-down attempts by governments and large organizations to influence society and bottom-up citizen articulations of needs and actions.
Toronto Metropolitan UniversityPublication 2024-03-25 Social Media Privacy in Canada This is the second report in the series based on an online survey of 1,500 Canadians. Building on the first report that provides a snapshot of the social media usage trends in Canada, this second report analyzes social media users’ privacy perceptions and expectations. (2018-06-01)
Toronto Metropolitan UniversityPublication 2024-03-25 Social Media and Political Engagement in Canada The report examines the ways online Canadian adults are engaging politically on social media. This is the third and final report based on a census-balanced survey of 1,500 Canadians using quota sampling by age, gender, and geographical region. The other two reports in this series are: "The State of Social Media in Canada 2017" and "Social Media Privacy in Canada". The series is published by the Social Media Lab, an interdisciplinary research lab at Ted Rogers School of Management, Ryerson University. The lab studies how social media is changing the ways in which people communicate, share information, conduct business and how these changes are impacting our society. (2018-12-12)
Toronto Metropolitan UniversityPublication 2024-03-25 Establishing TikTok as a Platform for Informal Learning: Evidence from Mixed-Methods Analysis of Creators and Viewers Over the past few years, participation in TikTok has rapidly increased, with a large number of people spending several hours per day consuming and creating content. In this study, we explore how such participation leads to informal learning on TikTok, as we explore patterns of how creators teach and consumers learn knowledge or skills on TikTok, making it a community conducive to sharing and learning knowledge or skills. Through a mixed methods study combining content analysis of TikTok videos and empirical investigation of TikTok users, we explore ways in which creators leverage platform affordances to share knowledge or skills on TikTok, and how their viewers learn from them. We observe successful teaching techniques, and produce recommendations for creators based on learners' preferences. Toronto Metropolitan University Publication 2024-01-01 To Share or Not to Share: Randomized Controlled Study of Misinformation Warning Labels on Social Media Toronto Metropolitan University Publication 2024-01-01 How COVID-19 Conspiracy Theories Spread on Twitter Toronto Metropolitan University Publication 2024-01-01 Social Media as Fragile State Toronto Metropolitan University Publication 2024-01-01
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