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 in 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.
Original language | English |
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Title of host publication | ACM international conference on information and knowledge management |
Place of Publication | New York, NY (US) |
Publisher | ACM |
Pages | 1649-1654 |
Number of pages | 6 |
ISBN (Print) | 978-1-4503-2263-8 |
DOIs | |
Publication status | Published - 27 Oct 2013 |
Event | 22nd ACM international conference on Conference on Information and Knowledge Management - Burlingame, CA, United States Duration: 27 Oct 2013 → 1 Nov 2013 |
Conference
Conference | 22nd ACM international conference on Conference on Information and Knowledge Management |
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Abbreviated title | CIKM 2013 |
Country/Territory | United States |
City | Burlingame, CA |
Period | 27/10/13 → 1/11/13 |