Determining credibility from social network structure

Authors:
Erica J. Briscoe;D. Scott Appling;Rudolph L. Mappus, IV;Heather Hayes
Affiliations:
Georgia Institute of Technology, Atlanta, GA;Georgia Institute of Technology, Atlanta, GA;Georgia Institute of Technology, Atlanta, GA;Georgia Institute of Technology, Atlanta, GA
Venue:
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Year:
2013

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Abstract

The increasing proliferation of social media results in users that are forced to 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, our study focuses on the determination of credibility in ego-centric networks based on subjects observing 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. We discuss the implications of the use of social network graph structural properties and use principal components analysis to visualize the reduced dimensional space.