Publication Type

Conference Proceeding Article

Publication Date

5-2013

Abstract

When a user retweets, there are three behavioral factors that cause the actions. They are the topic virality, user virality and user susceptibility. Topic virality captures the degree to which a topic attracts retweets by users. For each topic, user virality and susceptibility refer to the likelihood that a user attracts retweets and performs retweeting respectively. To model a set of observed retweet data as a result of these three topic specific factors, we first represent the retweets as a three-dimensional tensor of the tweet authors, their followers, and the tweets themselves. We then propose the V 2S model, a tensor factorization model, to simultaneously derive the three sets of behavioral factors. Our experiments on a real Twitter data set show that the V 2S model can effectively mine the behavioral factors of users and tweet topics during an election event. We also demonstrate that the V 2S model outperforms the other topic based models in retweet prediction.

Discipline

Databases and Information Systems | Numerical Analysis and Scientific Computing | Social Media

Research Areas

Data Management and Analytics

Publication

Proceedings of the 2013 SIAM International Conference on Data Mining: May 2-4, Austin, Texas

First Page

569

Last Page

577

ISBN

9781611972627

Identifier

10.1137/1.9781611972832.63

Publisher

SIAM

City or Country

Philadelphia, PA

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://dx.doi.org/10.1137/1.9781611972832.63

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