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Presentation
Tweet Properly: Analyzing Deleted Tweets to Understand and Identify Regrettable Ones
Conference WWW '16 25th International World Wide Web Conference Montreal, Canada
  • Lu Zhou, Wright State University - Main Campus
  • Wenbo Wang, Wright State University - Main Campus
  • Keke Chen, Wright State University - Main Campus
Document Type
Conference Proceeding
Publication Date
1-1-2016
Abstract
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.
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Presented at the 25th International Conference on the World Wide Web, Geneva, Switzerland, 2016.

DOI
10.1145/2872427.2883052
Citation Information
Lu Zhou, Wenbo Wang and Keke Chen. "Tweet Properly: Analyzing Deleted Tweets to Understand and Identify Regrettable Ones" Conference WWW '16 25th International World Wide Web Conference Montreal, Canada (2016) p. 603 - 612 ISSN: 9781450341431
Available at: http://works.bepress.com/keke_chen/51/