社区评论的可链接性探析
Exploring Linkablility of Community Reviewing
摘要：
全世界有大量的人阅读并为各种评论网站做出贡献。许多贡献者关心隐私是可以理解的;特别是关于评论（和帐户）在评论网站之间的可链接性。在本文中，我们研究了社区评论的可链接性，并试图回答这个问题：“匿名”评论在多大程度上是可链接的，即，可能是同一个作者写的基于一个非常大的一组评论从一个流行的网站（Yelp），我们表明，表面上匿名评论的高比例可以非常高的信心。尽管我们使用非常简单的模型和同样简单的功能集。我们的研究表明，贡献者在评论中可靠地暴露了他们的身份。这对不同评论网站之间的交叉引用账户具有重要意义。此外，我们研究中使用的技术可以被评论网站采用，以向贡献者提供有关其评论隐私的反馈。
英文摘要：
Large numbers of people all over the world read and contribute to various review sites. Many contributors are understandably concerned about privacy; specifically, about linkability of reviews (and accounts) across review sites. In this paper, we study linkability of community reviewing and try to answer the question: to what extent are "anonymous" reviews linkable, i.e., likely authored by the same contributor? Based on a very large set of reviews from a popular site (Yelp), we show that a high percentage of ostensibly anonymous reviews can be linked with very high confidence. This is despite the fact that we use very simple models and equally simple features set. Our study suggests that contributors reliably expose their identities in reviews. This has important implications for cross-referencing accounts between different review sites. Also, techniques used in our study could be adopted by review sites to give contributors feedback about privacy of their reviews.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
