Publication
WebSci 2015
Conference paper

TweetSense: Context recovery for orphan tweets by exploiting social signals in Twitter

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Abstract

As the popularity of Twitter, and the volume of tweets increased dramatically, hashtags have naturally evolved to become a de facto context providing/categorizing mechanism on Twitter. Despite their wide-spread adoption, fueled in part by hashtag recommendation systems, lay users continue to generate tweets without hashtags. When such "orphan" tweets show up in a (browsing) user's time-line, it is hard to make sense of their context. In this paper, we present a system called TweetSense which aims to rectify such orphan tweeets by recovering their context in terms of their missing hashtags. TweetSense enables this context recovery by using both the content and social network features of the orphan tweet. We characterize the context recovery problem, present the details of TweetSense and present a systematic evaluation of its effectiveness over a 7 million tweet corpus.

Date

28 Jun 2015

Publication

WebSci 2015

Authors

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