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Social Network Derived Credibility

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Recommendation and Search in Social Networks

Part of the book series: Lecture Notes in Social Networks ((LNSN))

Abstract

The increasing use of social media results in users that must ascertain the truthfulness of information that they encounter from unknown sources using a variety of indicators (e.g., explicit ratings, profile information, etc.). Through human-subject experimentation with an online social network-style platform, we focus on the determination of credibility in ego-centric networks, where participants are able to observe salient social network properties, such as degree centrality and geodesic distance. Using manipulated social network graphs, we find that corroboration and degree centrality are most utilized by subjects as indicators of credibility. utilized by subjects as indicators of credibility. We discuss the implications of the use of social network structural properties, use principal components analysis to visualize the reduced dimensional feature space, and analyze how credibility changes per property according to the “Big 5” theory of personality.

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Acknowledgments

This material is based on work supported in part by the Defense Advanced Research Projects Agency (DARPA) under Contract No. W911NF-12-1-0043. Any opinions, findings, and conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of DARPA or the U.S. Government.

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Authors and Affiliations

  1. Georgia Tech, 220 North Avenue, Atlanta, GA, USA

    Erica J. Briscoe, Darren Scott Appling & Heather Hayes

Authors
  1. Erica J. Briscoe
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  2. Darren Scott Appling
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  3. Heather Hayes
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Corresponding author

Correspondence to Erica J. Briscoe .

Editor information

Editors and Affiliations

  1. Department of Computer Engineering, Bilkent University, Ankara, Turkey

    Özgür Ulusoy

  2. Statistics and Computer Information Systems, Baruch College, CUNY, New York, New York, USA

    Abdullah Uz Tansel

  3. Department of Computer Engineering, Bilkent University, Ankara, Turkey

    Erol Arkun

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Briscoe, E.J., Appling, D.S., Hayes, H. (2015). Social Network Derived Credibility. In: Ulusoy, Ö., Tansel, A., Arkun, E. (eds) Recommendation and Search in Social Networks. Lecture Notes in Social Networks. Springer, Cham. https://doi.org/10.1007/978-3-319-14379-8_4

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  • DOI: https://doi.org/10.1007/978-3-319-14379-8_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-14378-1

  • Online ISBN: 978-3-319-14379-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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