Abstract
Customers learn about restaurants in various ways, and integrating this disparate information could give them access to a greater diversity of perspectives. Conflicting opinions between restaurant-review platforms are inevitable. However, such conflicts’ influences on users’ perceptions remain unclear, especially when the opinion of a user’s preferred platform conflicts with the majority of others. This study’s experiment with a sample of 304 users found that, when such situations occurred, the preferred platform’s influence differed depending on whether the user was shown a sequence of whole-platform aggregations vs. a sequence of individual reviews drawn from multiple platforms. That is, the participants accepted the majority view most of the time, but when looking at aggregated lists, if their preferred platform expressed a minority positive opinion based on a high quantity of reviews, that minority opinion could prevail over the majority one. Between-platform conflicts were also found to have a greater impact on user reactions than within-platform ones did.
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No potential conflict of interest was reported by the author(s).
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Tzu-Hao Lin
Tzu-Hao Lin received the M.S. degree in Computer Science, National Chiao Tung University (NCTU). He is currently working in Mediatek as a software engineer, mainly responsible for the development of automation tools and data analysis & visualization. His research interests mainly focused on human computer interaction on mobile devices.
Yen-Yun Liu
Yen-Yun Liu received her B.S. degree in Psychology from National Taiwan University (NTU), Taipei, Taiwan. She is currently pursuing an M.Sc. degree in Applied Cognitive Psychology at Utrecht University, Utrecht, the Netherlands. Her research interests include mobile crowdsourcing, social robotics, and autonomous driving.
Hong-Han Shuai
Hong-Han Shuai received the B.S., M.S. and Ph.D. degree from the Department of Electrical Engineering, National Taiwan University (NTU), Taiwan He is now an associate professor in National Yang Ming Chiao Tung University (NYCU), Taiwan. His research interests are multimedia processing, machine learning, social network analysis, and data mining.
Fang-Hsin Hsu
Fang Hsin Hsu received the B.S. degree in Computer Science & Information Engineering, National Central University (NCU). She is currently studying for her M.S. degree at the Institute of Network Engineering at NYCU. Her research interest is human computer interaction (HCI), with a focus on attention research.
Yung-Ju Chang
Yung-Ju (Stanley) Chang is an associate professor at the Department of Computer Science at NYCU. He received his M.S. and Ph.D. degree in Information Science from the University of Michigan. His research interest is human computer interaction (HCI), with a focus on attention research in computer-mediated communication.