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SUMMARY:TBC - Mohsen Mosleh\, University of Oxford
DTSTART:20260515T110000Z
DTEND:20260515T123000Z
UID:TALK246568@talks.cam.ac.uk
CONTACT:Psychology Reception
DESCRIPTION:In this talk\, I present two complementary lines of work that 
 together illuminate how information spreads across platforms and is evalua
 ted through human–AI interaction. First\, drawing on over 10 million new
 s-link posts shared across seven major platforms including mainstream\, al
 ternative\, and decentralized systems\, I show that relationships between 
 political orientation\, engagement\, and news quality are highly platform-
 specific rather than universal. While political engagement follows an “e
 cho-platform” pattern that depends on a platform’s dominant ideology\,
  the tendency for lower-quality news to receive higher per-post engagement
  is strikingly consistent across platforms\, even in the absence of rankin
 g algorithms\, pointing to user preferences rather than algorithmic bias. 
 Second\, I turn to the rapidly growing role of large language models embed
 ded in social media\, analyzing nearly 1.7 million real-world fact-checkin
 g requests to AI systems on X. I show that human–AI fact-checking is alr
 eady operating at scale\, exhibits partisan asymmetries in both usage and 
 trust\, and produces belief updates comparable to professional fact-checki
 ng\, while also becoming entangled with polarization and model identity. T
 ogether\, these findings highlight the need to study social media as a mul
 ti-platform ecosystem\, where both information exposure and judgment emerg
 e from interactions among users\, platforms\, and increasingly\, AI system
 s themselves.\n\nHost: Dr Jon Roozenbeek \n\nThis talk will be recorded an
 d uploaded to the Zangwill Club "Youtube channel":https://www.youtube.com/
 @zangwill_club in due course.
LOCATION:Ground Floor Lecture Theatre\, Department of  Psychology
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