Popularity Effect in User-Generated Content: Evidence from Online Product Reviews

• 成果类型: Review
• 署名作者: Goes, Paulo B.; Lin, Mingfeng; Yeung, Ching-man Au
• 署名单位: University of Arizona
• 刊物名称: INFORMATION SYSTEMS RESEARCH
• ISSN/ISSBN: 1047-7047
• DOI: 10.1287/isre.2013.0512
• 发表日期: 2014
• 页码: 222-238
• 关键词: word-of-mouth; knowledge contribution; social-influence; panel-data; communities; network; DYNAMICS; IDENTITY; feedback; IMPACT

摘要

Online product reviews are increasingly important for consumer decisions, yet we still know little about how reviews are generated in the first place. In an effort to gather more reviews, many websites encourage user interactions such as allowing one user to subscribe to another. Do these interactions actually facilitate the generation of product reviews? More importantly, what kind of reviews do such interactions induce? We study these questions using data from one of the largest product review websites where users can subscribe to one another. By applying both panel data and a flexible matching method, we find that as users become more popular, they produce more reviews and more objective reviews; however, their numeric ratings also systematically change and become more negative and more varied. Such trade-off has not been previously documented and has important implications for both product review and other user-generated content websites.