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 publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages441-448
Number of pages8
Volume7812 LNCS
DOIs
StatePublished - 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)03029743
ISSN (Electronic)16113349

Other

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

Fingerprint

Social Media
Credibility
Tsunamis
Hurricanes
Disasters
Credibility Measure
Industry
Tsunami
User Profile
Disaster
Japan

Keywords

  • Behavior Analysis
  • Information Credibility
  • Misinformation

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Abbasi, M. A., & Liu, H. (2013). Measuring user credibility in social media. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7812 LNCS, 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

Measuring user credibility in social media. / Abbasi, Mohammad Ali; Liu, Huan.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7812 LNCS 2013. p. 441-448 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7812 LNCS).

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

Abbasi, MA & Liu, H 2013, Measuring user credibility in social media. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 7812 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7812 LNCS, pp. 441-448, 6th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction, SBP 2013, Washington, DC, United States, 4/2/13. https://doi.org/10.1007/978-3-642-37210-0_48
Abbasi MA, Liu H. Measuring user credibility in social media. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7812 LNCS. 2013. p. 441-448. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-37210-0_48
Abbasi, Mohammad Ali ; Liu, Huan. / Measuring user credibility in social media. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7812 LNCS 2013. pp. 441-448 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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