Predicting user participation in social networking sites

Qingchao Kong, Wenji Mao, Dajun Zeng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Social networking sites provide a convenient way for users to participate in discussion groups and communicate with others. While users situate in and enjoy such a social environment, it is important for various security related applications to understand, model and analyze participating users' behavior. In this paper, we make an attempt to model and predict user participation behavior in discussion groups of social networking sites. Our work employs a feature-based approach, which considers four types of features: thread features, content similarity, user behavior and social features. We conduct an empirical study on a popular social networking site in China, Douban.com. The experimental results show the effectiveness of our approach.

Original languageEnglish (US)
Title of host publicationIEEE ISI 2013 - 2013 IEEE International Conference on Intelligence and Security Informatics: Big Data, Emergent Threats, and Decision-Making in Security Informatics
Pages154-156
Number of pages3
DOIs
StatePublished - 2013
Event11th IEEE International Conference on Intelligence and Security Informatics, IEEE ISI 2013 - Seattle, WA, United States
Duration: Jun 4 2013Jun 7 2013

Other

Other11th IEEE International Conference on Intelligence and Security Informatics, IEEE ISI 2013
CountryUnited States
CitySeattle, WA
Period6/4/136/7/13

Keywords

  • behavior modeling and prediction
  • social networking sites
  • user participation

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems

Cite this

Kong, Q., Mao, W., & Zeng, D. (2013). Predicting user participation in social networking sites. In IEEE ISI 2013 - 2013 IEEE International Conference on Intelligence and Security Informatics: Big Data, Emergent Threats, and Decision-Making in Security Informatics (pp. 154-156). [6578807] https://doi.org/10.1109/ISI.2013.6578807

Predicting user participation in social networking sites. / Kong, Qingchao; Mao, Wenji; Zeng, Dajun.

IEEE ISI 2013 - 2013 IEEE International Conference on Intelligence and Security Informatics: Big Data, Emergent Threats, and Decision-Making in Security Informatics. 2013. p. 154-156 6578807.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Kong, Q, Mao, W & Zeng, D 2013, Predicting user participation in social networking sites. in IEEE ISI 2013 - 2013 IEEE International Conference on Intelligence and Security Informatics: Big Data, Emergent Threats, and Decision-Making in Security Informatics., 6578807, pp. 154-156, 11th IEEE International Conference on Intelligence and Security Informatics, IEEE ISI 2013, Seattle, WA, United States, 6/4/13. https://doi.org/10.1109/ISI.2013.6578807
Kong Q, Mao W, Zeng D. Predicting user participation in social networking sites. In IEEE ISI 2013 - 2013 IEEE International Conference on Intelligence and Security Informatics: Big Data, Emergent Threats, and Decision-Making in Security Informatics. 2013. p. 154-156. 6578807 https://doi.org/10.1109/ISI.2013.6578807
Kong, Qingchao ; Mao, Wenji ; Zeng, Dajun. / Predicting user participation in social networking sites. IEEE ISI 2013 - 2013 IEEE International Conference on Intelligence and Security Informatics: Big Data, Emergent Threats, and Decision-Making in Security Informatics. 2013. pp. 154-156
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