Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
Tweet, Tweet, Retweet: Conversational Aspects of Retweeting on Twitter
HICSS '10 Proceedings of the 2010 43rd Hawaii International Conference on System Sciences
Topical semantics of twitter links
Proceedings of the fourth ACM international conference on Web search and data mining
Predicting popular messages in Twitter
Proceedings of the 20th international conference companion on World wide web
Information credibility on twitter
Proceedings of the 20th international conference on World wide web
Influence and passivity in social media
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part III
TV program detection in tweets
Proceedings of the 11th european conference on Interactive TV and video
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Twitter, a popular social networking service, enables its users to not only send messages but re-broadcast or retweet a message from another Twitter user to their own followers. Considering the number of times that a message is retweeted across Twitter is a straightforward way to estimate how interesting it is. However, a considerable number of messages in Twitter with high retweet counts are actually mundane posts by celebrities that are of interest to themselves and possibly their followers. In this paper, we leverage retweets as implicit relationships between Twitter users and messages and address the problem of automatically finding messages in Twitter that may be of potential interest to a wide audience by using link analysis methods that look at more than just the sheer number of retweets. Experimental results on real world data demonstrate that the proposed method can achieve better performance than several baseline methods.