人气
用户生成的内容
计算机科学
产品(数学)
匹配(统计)
万维网
数据科学
互联网隐私
社会化媒体
几何学
心理学
数学
社会心理学
统计
作者
Paulo Góes,Mingfeng Lin,Ching‐man Au Yeung
出处
期刊:Information Systems Research
[Institute for Operations Research and the Management Sciences]
日期:2014-06-01
卷期号:25 (2): 222-238
被引量:314
标识
DOI:10.1287/isre.2013.0512
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.
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