Examining the Impacts of Airbnb's Review Policy Change on Listing Reviews

Reza Mousavi, K. Zhao
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引用次数: 2

Abstract

In July 2014, Airbnb, one of the biggest firms in the sharing economy, decided to change the way the guests and the hosts review each other on the platform. Before this change, the guests and hosts were able to post reviews about their experiences asynchronously - the host/guest would be able to see the other party’s review whenever it was posted. The new review policy though, rolled out a simultaneous review system in which reviews are viewable only after both the host and the guest posting their own reviews. Our aim in this study was to examine the impacts of this new review policy on guest reviews. Using Regression Discontinuity Design, Panel Data Analysis and a variety of techniques in the text analytics domain, we discovered that the new review policy made the reviews more diverse in terms of topics discussed in the reviews, lengthier, more objective, less positive, and more diverse in terms of their sentiment. Interestingly, we also discovered that the review policy had a long-lasting impact on the constructs related to personal opinions (i.e., sentiment and the diversity of sentiment in the reviews). However, the impact of review policy on informational content (i.e., diversity of topics, depth, and objectivity of the reviews) was short-lived.
考察Airbnb审核政策变化对房源审核的影响
2014年7月,共享经济领域最大的公司之一Airbnb决定改变客人和房东在平台上相互评价的方式。在此更改之前,客人和主人可以异步发布关于他们体验的评论——无论何时发布评论,主人/客人都可以看到对方的评论。然而,新的评论政策推出了一个同步评论系统,只有在主人和客人都发表了自己的评论之后,评论才能被看到。我们在这项研究中的目的是检查这项新的评论政策对客人评论的影响。使用回归不连续设计,面板数据分析和文本分析领域的各种技术,我们发现新的评论政策使评论在评论中讨论的主题方面更加多样化,更长,更客观,不那么积极,并且在他们的情绪方面更加多样化。有趣的是,我们还发现评论政策对与个人意见相关的构念(即评论中的情绪和情绪的多样性)有持久的影响。然而,审查政策对信息内容(即主题的多样性、深度和审查的客观性)的影响是短暂的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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