Tweet Properly: Analyzing Deleted Tweets to Understand and Identify Regrettable Ones
Tweet Properly: Analyzing Deleted Tweets to Understand and Identify Regrettable Ones
复制标题
正确发推文：分析已删除的推文以了解和识别令人遗憾的推文
DOI：
10.1145/2872427.2883052
复制
发表时间：
2016
期刊：
影响因子：
--
通讯作者：
Keke Chen
中科院分区：
文献类型：
--
作者：
Lu Zhou;Wenbo Wang;Keke Chen
不适当的推文可能会对作者的声誉或隐私造成严重损害。然而，许多用户直到发布这些推文才意识到负面后果。发布的推文具有持久的影响，可能无法通过简单的删除来消除，因为其他用户可能已经阅读了它们，或者第三方推文分析平台已经缓存了它们。遗憾的推文，即，带有可识别的遗憾内容的推文对作者造成的伤害最大，因为其他用户很容易注意到它们。本文研究了如何通过内容和用户的历史删除模式来识别普通个人用户发布的遗憾推文。我们根据他们的发布、删除、关注者和朋友统计数据来识别正常的个人用户。我们手动检查这些用户的一组随机抽样删除的推文，以识别令人遗憾的推文，并了解相应的令人遗憾的原因。通过应用基于内容的特征和个性化的基于历史的特征，我们开发了分类器，可以有效地预测令人遗憾的推文。
Inappropriate tweets can cause severe damages on authors' reputation or privacy. However, many users do not realize the negative consequences until they publish these tweets. Published tweets have lasting effects that may not be eliminated by simple deletion because other users may have read them or third-party tweet analysis platforms have cached them. Regrettable tweets, i.e., tweets with identifiable regrettable contents, cause the most damage on their authors because other users can easily notice them. In this paper, we study how to identify the regrettable tweets published by \emph{normal individual users} via the contents and users' historical deletion patterns. We identify normal individual users based on their publishing, deleting, followers and friends statistics. We manually examine a set of randomly sampled deleted tweets from these users to identify regrettable tweets and understand the corresponding regrettable reasons. By applying content-based features and personalized history-based features, we develop classifiers that can effectively predict regrettable tweets.