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UID:20260412T181011EDT-0900cZEVWv@132.216.98.100
DTSTAMP:20260412T221011Z
DESCRIPTION:Zaiyan Wei\n\nMitch Daniels School of Business - Perdue Univers
 ity\n\nGuiding without Generating: Artificial Intelligence (AI)-Enabled To
 pic Nudges in Online Reviews\n\nDate: Friday\, April 10\, 2026\n	Time: 10:3
 0 am - 12:00 pm EDT\n	Location: Armstrong building - Room 255\n\nAll are co
 rdially invited to attend.\n\n\nAbout:\n\nDigital platforms increasingly f
 ace a common challenge: how to elicit richer and more useful user-generate
 d content (UGC) without fully automating content production. We study this
  question in the context of online reviews by examining Yelp’s introductio
 n of an artificial intelligence (AI)-enabled topic nudging tool in 2023. T
 he feature provides real-time prompts to guide review writers in addressin
 g key dimensions of the dining experience as they compose their reviews. U
 sing more than 1.5 million reviews and a differences-in-differences design
 \, we find that AI-enabled topic nudges significantly reshape the generati
 on of reviews. First\, they expand topical coverage\, particularly for und
 errepresented aspects such as service and ambiance\, and lead to longer re
 views while reducing overall review volume. Second\, reviews become more t
 extually complex and less readable\, and they receive fewer helpfulness vo
 tes on average. Further analysis shows that the decline in perceived helpf
 ulness is mitigated when review content remains concentrated on a dominant
  dimension\, highlighting the importance of informational focus. Lastly\, 
 we find that the impacts are heterogeneous: less experienced users expand 
 review length and topical coverage more significantly\, whereas experience
 d users exhibit greater complexity and larger declines in perceived helpfu
 lness. Our findings extend research on AI and user-generated content by hi
 ghlighting a distinct mode of AI deployment\, i.e.\, guiding rather than g
 enerating human contributions\, and by revealing its benefits and unintend
 ed consequences for platform design.\n
DTSTART:20260410T143000Z
DTEND:20260410T160000Z
LOCATION:Room 255\, Donald E. Armstrong Building\, CA\, QC\, Montreal\, H3A
  3L1\, 3420 rue McTavish
SUMMARY:Business & Management Research Centre: Zaiyan Wei
URL:https://www.mcgill.ca/desautels/channels/event/business-management-rese
 arch-centre-zaiyan-wei-372260
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