Abstract

People increasingly use social media to get first-hand news and information. During disasters such as Hurricane Sandy and the tsunami in Japan people used social media to report injuries as well as send out their requests. During social movements such as Occupy Wall Street (OWS) and the Arab Spring, people extensively used social media to organize their events and spread the news. As more people rely on social media for political, social, and business events, it is more susceptible to become a place for evildoers to use it to spread misinformation and rumors. Therefore, users have the challenge to discern which piece of information is credible or not. They also need to find ways to assess the credibility of information. This problem becomes more important when the source of the information is not known to the consumer. In this paper we propose a method to measure user credibility in social media. We study the situations in which we cannot assess the credibility of the content or the credibility of the user (source of the information) based on the user's profile. We propose the CredRank algorithm to measure user credibility in social media. The algorithm analyzes social media users' online behavior to measure their credibility.

Original languageEnglish (US)
Title of host publicationSocial Computing, Behavioral-Cultural Modeling and Prediction - 6th International Conference, SBP 2013, Proceedings
Pages441-448
Number of pages8
DOIs
StatePublished - Mar 14 2013
Event6th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction, SBP 2013 - Washington, DC, United States
Duration: Apr 2 2013Apr 5 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7812 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other6th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction, SBP 2013
CountryUnited States
CityWashington, DC
Period4/2/134/5/13

Keywords

  • Behavior Analysis
  • Information Credibility
  • Misinformation

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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    Abbasi, M. A., & Liu, H. (2013). Measuring user credibility in social media. In Social Computing, Behavioral-Cultural Modeling and Prediction - 6th International Conference, SBP 2013, Proceedings (pp. 441-448). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7812 LNCS). https://doi.org/10.1007/978-3-642-37210-0_48