{"id":16916,"date":"2026-03-03T09:20:02","date_gmt":"2026-03-03T08:20:02","guid":{"rendered":"https:\/\/www.uni.lu\/research-en\/?post_type=events&p=16916"},"modified":"2026-04-15T08:01:19","modified_gmt":"2026-04-15T06:01:19","slug":"doctoral-defence-yuwei-chuai","status":"publish","type":"events","link":"https:\/\/www.uni.lu\/research-en\/events\/doctoral-defence-yuwei-chuai\/","title":{"rendered":"Doctoral Defence: Yuwei CHUAI"},"content":{"rendered":"\n
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The Doctoral School in Science and Engineering<\/a> is happy to invite you to Yuwei CHUAI\u2019s defence entitled<\/p>\n\n\n\n

\nComputational Analysis of Misinformation Engagement and Interventions on Social Media<\/h2>\n\n\n\n

Supervisor<\/strong>: Assoc. Prof Gabriele LENZINI<\/a><\/p>\n\n\n\n

The widespread use of social media has transformed how information is created, shared, and consumed, but it has also enabled the rapid diffusion of misinformation with serious consequences for public health, democratic processes, and social trust. Despite extensive research on misinformation, important gaps remain in understanding how users engage with misleading content during health crises, how fact-checking organizations select claims for verification, and how effective emerging fact-checking interventions are in real-world settings. This thesis addresses these gaps by examining misinformation diffusion and fact-checking practices on social media, with a particular focus on the role and effectiveness of crowdsourced fact-checking approach, i.e., the Community Notes system deployed on X (formerly Twitter).<\/p>\n\n\n\n

 First, the thesis advances the understanding of user engagement with misinformation during health crises. Using the COVID-19 pandemic as a case study, it shows that misinformation often spans multiple topics and incorporates conspiracy narratives, which increases its attractiveness to users. Crucially, the thesis distinguishes between different user types on social media — those who share external news items and those who react to them on X — and demonstrates that these groups exhibit different engagement patterns. While news sharers contribute to the persistence of misinformation over time, post viewers are more likely to engage with content characterized by topic diversity and conspiratorial framing.<\/p>\n\n\n\n