Similarity measure and instance selection for collaborative filtering
WWW '03 Proceedings of the 12th international conference on World Wide Web
Content-boosted collaborative filtering for improved recommendations
Eighteenth national conference on Artificial intelligence
Trust-based agent community for collaborative recommendation
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
News cues: Information scent and cognitive heuristics: Research Articles
Journal of the American Society for Information Science and Technology
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
CHI '10 Extended Abstracts on Human Factors in Computing Systems
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Maater: crowdsourcing to improve online journalism
CHI '13 Extended Abstracts on Human Factors in Computing Systems
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Advancements in collaborative filtering and related technologies have resulted in the ubiquitous presence of other users' opinions and actions on a variety of Websites and portals, ranging from news to music to photo sites. But, do these cues about others' behaviors guide our own decisions online? Our lab group has begun exploring this "bandwagon effect" from a variety of perspectives. In one pilot study reported here, outcomes such as purchase intention and attitudes toward products on an e-commerce site are dictated by user perceptions of others' opinions about the site's products. Empirical determination of the cues triggered by collaborative filtering technologies and the psychological mechanisms by which they lead to bandwagon effects have important implications for interface design of technologies that display user input.