Modeling users' preferences and social links in social networking services: A joint-evolving perspective

Le Wu, Yong Ge, Qi Liu, Enhong Chen, Bai Long, Zhenya Huang

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

31 Scopus citations

Abstract

Researchers have long converged that the evolution of a Social Networking Service (SNS) platform is driven by the interplay between users' preferences (reflected in user-item consumption behavior) and the social network structure (reflected in user-user interaction behavior), with both kinds of users' behaviors change from time to time. However, traditional approaches either modeled these two kinds of behaviors in an isolated way or relied on a static assumption of a SNS. Thus, it is still unclear how do the roles of users' historical preferences and the dynamic social network structure affect the evolution of SNSs. Furthermore, can jointly modeling users' temporal behaviors in SNSs benefit both behavior prediction tasks? In this paper, we leverage the underlying social theories (i.e., social influence and the homophily effect) to investigate the interplay and evolution of SNSs. We propose a probabilistic approach to fuse these social theories for jointly modeling users' temporal behaviors in SNSs. Thus our proposed model has both the explanatory ability and predictive power. Experimental results on two real-world datasets demonstrate the effectiveness of our proposed model.

Original languageEnglish (US)
Title of host publication30th AAAI Conference on Artificial Intelligence, AAAI 2016
PublisherAAAI press
Pages279-286
Number of pages8
ISBN (Electronic)9781577357605
StatePublished - 2016
Externally publishedYes
Event30th AAAI Conference on Artificial Intelligence, AAAI 2016 - Phoenix, United States
Duration: Feb 12 2016Feb 17 2016

Publication series

Name30th AAAI Conference on Artificial Intelligence, AAAI 2016

Other

Other30th AAAI Conference on Artificial Intelligence, AAAI 2016
Country/TerritoryUnited States
CityPhoenix
Period2/12/162/17/16

ASJC Scopus subject areas

  • Artificial Intelligence

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