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OTM Confederated International Conferences "On the Move to Meaningful Internet Systems"

OTM 2015: On the Move to Meaningful Internet Systems: OTM 2015 Conferences pp 473–482Cite as

A Model for Identifying Misinformation in Online Social Networks

Part of the Lecture Notes in Computer Science book series (LNISA,volume 9415)

Abstract

Online Social Networks (OSNs) have become increasingly popular means of information sharing among users. The spread of news regarding emergency events is common in OSNs and so is the spread of misinformation related to the event. We define as misinformation any false or inaccurate information that is spread either intentionally or unintentionally. In this paper we study the problem of misinformation identification in OSNs, and we focus in particular on the Twitter social network. Based on user and tweets characteristics, we build a misinformation detection model that identifies suspicious behavioral patterns and exploits supervised learning techniques to detect misinformation. Our extensive experimental results on 80294 unique tweets and 59660 users illustrate that our approach effectively identifies misinformation during emergencies. Furthermore, our model manages to timely identify misinformation, a feature that can be used to limit the spread of the misinformation.

S. Antoniadis—Part of this work was performed when this author was at Athens University of Economics and Business.

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  • DOI: 10.1007/978-3-319-26148-5_32
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Author information

Authors and Affiliations

  1. Nokia Solutions and Networks Hellas A.E., Athens, Greece

    Sotirios Antoniadis

  2. Deptartment of Informatics, Athens University of Economics and Business, Athens, Greece

    Iouliana Litou & Vana Kalogeraki

Authors
  1. Sotirios Antoniadis
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  2. Iouliana Litou
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  3. Vana Kalogeraki
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Corresponding author

Correspondence to Iouliana Litou .

Editor information

Editors and Affiliations

  1. Trinity College Dublin, Dublin 2, Iran

    Christophe Debruyne

  2. University of Lorraine, Vandoeuvre-les-Nancy Cedex, France

    Hervé Panetto

  3. TU Graz, Graz, Austria

    Robert Meersman

  4. La Trobe University, Melbourne, Australia

    Tharam Dillon

  5. PROFACTOR GmbH, Steyr-Gleink, Austria

    Georg Weichhart

  6. Drexel University, Philadelphia, Pennsylvania, USA

    Yuan An

  7. Università degli Studi di Milano, Crema, Italy

    Claudio Agostino Ardagna

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Antoniadis, S., Litou, I., Kalogeraki, V. (2015). A Model for Identifying Misinformation in Online Social Networks. In: , et al. On the Move to Meaningful Internet Systems: OTM 2015 Conferences. OTM 2015. Lecture Notes in Computer Science(), vol 9415. Springer, Cham. https://doi.org/10.1007/978-3-319-26148-5_32

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  • DOI: https://doi.org/10.1007/978-3-319-26148-5_32

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