Detecting rumors through modeling information propagation networks in a social media environment

Yang Liu, Songhua Xu, Georgia Tourassi

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

8 Scopus citations

Abstract

In the midst of today’s pervasive influence of social media content and activities, information credibility has increasingly become a major issue. Accordingly, identifying false information, e.g. rumors circulated in social media environments, attracts expanding research attention and growing interests. Many previous studies have exploited user-independent features for rumor detection. These prior investigations uniformly treat all users relevant to the propagation of a social media message as instances of a generic entity. Such a modeling approach usually adopts a homogeneous network to represent all users, the practice of which ignores the variety across an entire user population in a social media environment. Recognizing this limitation of modeling methodologies, this study explores user-specific features in a social media environment for rumor detection. The new approach hypothesizes that whether a user tends to spread a rumor is dependent upon specific attributes of the user in addition to content characteristics of the message itself. Under this hypothesis, information propagation patterns of rumors versus those of credible messages in a social media environment are systematically differentiable. To explore and exploit this hypothesis, we develop a new information propagation model based on a heterogeneous user representation for rumor recognition. The new approach is capable of differentiating rumors from credible messages through observing distinctions in their respective propagation patterns in social media. Experimental results show that the new information propagation model based on heterogeneous user representation can effectively distinguish rumors from credible social media content.

Original languageEnglish (US)
Title of host publicationSocial Computing, Behavioral-Cultural Modeling, and Prediction - 8th International Conference, SBP 2015, Proceedings
EditorsKevin Xu, Nitin Agarwal, Nathaniel Osgood
PublisherSpringer Verlag
Pages121-130
Number of pages10
ISBN (Electronic)9783319162676
DOIs
StatePublished - 2015
Event8th International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction, SBP 2015 - Washington, United States
Duration: Mar 31 2015Apr 3 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9021
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other8th International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction, SBP 2015
CountryUnited States
CityWashington
Period3/31/154/3/15

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Keywords

  • Heterogeneous user representation and modelling
  • Information credibility in social media
  • Information propagation model
  • Rumor detection

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