Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Why we twitter: understanding microblogging usage and communities
Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis
What is Twitter, a social network or a news media?
Proceedings of the 19th international conference on World wide web
TwitterMonitor: trend detection over the twitter stream
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Empirical study of topic modeling in Twitter
Proceedings of the First Workshop on Social Media Analytics
See what's enBlogue: real-time emergent topic identification in social media
Proceedings of the 15th International Conference on Extending Database Technology
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Twitter has attracted millions of users that generate a humongous flow of information at constant pace. The research community has thus started proposing tools to extract meaningful information from tweets. In this paper, we take a different angle from the mainstream of previous works: we explicitly target the analysis of the timeline of tweets from "single users". We define a framework - named TUCAN - to compare information offered by the target users over time, and to pinpoint recurrent topics or topics of interest. First, tweets belonging to the same time window are aggregated into "bird songs". Several filtering procedures can be selected to remove stop-words and reduce noise. Then, each pair of bird songs is compared using a similarity score to automatically highlight the most common terms, thus highlighting recurrent or persistent topics. TUCAN can be naturally applied to compare bird song pairs generated from timelines of different users. By showing actual results for both public profiles and anonymous users, we show how TUCAN is useful to highlight meaningful information from a target user's Twitter timeline.