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

被引:244
|
作者
Goes, Paulo B. [1 ]
Lin, Mingfeng [1 ]
Yeung, Ching-man Au [2 ]
机构
[1] Univ Arizona, Eller Coll Management, Tucson, AZ 85721 USA
[2] Axon Labs Ltd, Hong Kong, Hong Kong, Peoples R China
关键词
product reviews; user-generated content; online community; opinion leader; social media; popularity; text mining; matching; WORD-OF-MOUTH; KNOWLEDGE CONTRIBUTION; SOCIAL-INFLUENCE; PANEL-DATA; COMMUNITIES; NETWORK; DYNAMICS; IDENTITY; FEEDBACK; IMPACT;
D O I
10.1287/isre.2013.0512
中图分类号
G25 [图书馆学、图书馆事业]; G35 [情报学、情报工作];
学科分类号
1205 ; 120501 ;
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.
引用
收藏
页码:222 / 238
页数:17
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