Publication Type
Conference Proceeding Article
Version
acceptedVersion
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
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
Citation
HOANG, Tuan-Anh and LIM, Ee Peng.
Retweeting: An act of viral users, susceptible users, or viral topics?. (2013). Proceedings of the 2013 SIAM International Conference on Data Mining: May 2-4, Austin, Texas. 569-577.
Available at: https://ink.library.smu.edu.sg/sis_research/1965
Copyright Owner and License
LARC
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
http://doi.org/10.1137/1.9781611972832.63
Included in
Databases and Information Systems Commons, Numerical Analysis and Scientific Computing Commons, Social Media Commons
