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

机译:用户生成内容中的“人气效应”:来自在线产品评论的证据

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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.
机译:在线产品评论对于消费者的决定越来越重要,但是我们对起初如何产生评论仍然知之甚少。为了收集更多评论,许多网站鼓励用户进行交互,例如允许一个用户订阅另一个。这些互动是否真的促进了产品评论的生成?更重要的是,这种互动会引起什么样的评论?我们使用来自最大的产品评论网站之一的数据来研究这些问题,用户可以在该网站上互相订阅。通过同时应用面板数据和灵活的匹配方法,我们发现随着用户的普及,他们会产生更多的评论和更客观的评论。但是,它们的数字等级也会有系统地变化,变得越来越负面和越来越多样化。这种折衷以前没有记录,对产品评论和其他用户生成的内容网站都具有重要意义。

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