Originator or propagator?: incorporating social role theory into topic models for twitter content analysis

Authors:
Xin Wayne Zhao;Jinpeng Wang;Yulan He;Jian-Yun Nie;Xiaoming Li
Affiliations:
Peking University, Beijing, China;Peking University, Beijing, China;Aston University, Birmingham, United Kingdom;Montreal University, Montreal, Canada;Peking University, Beijing, China
Venue:
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Year:
2013

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Abstract

A large number of studies have been devoted to modeling the contents and interactions between users on Twitter. In this paper, we propose a method inspired from Social Role Theory (SRT), which assumes that a user behaves differently with different roles in the generation process of Twitter content. We consider the two most distinctive social roles on Twitter: originator and propagator, who respectively posts original messages and retweets or forwards the messages from others. In addition, we also consider role-specific social interactions, especially implicit interactions between users who share some common interests. All the above elements are integrated into a novel regularized topic model. We evaluate the proposed method on real Twitter data. The results show that our method is more effective than the existing ones which do not distinguish social roles.