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Measurement of Online Discussion Authenticity within Online Social Media

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Published:31 July 2017Publication History

ABSTRACT

In this paper, we propose an approach for estimating the authenticity of online discussions based on the similarity of online social media (OSM) accounts participating in the online discussion to known abusers and legitimate accounts. Our method uses similarity functions for the analysis and classification of OSM accounts. The proposed methods are demonstrated using Twitter data collected for this study and a previously published Arabic Honeypot dataset. The data collected during this study includes manually labeled accounts and a ground truth collection of abusers from crowdturfing platforms. Demonstration of the discussion topic's authenticity, derived from account similarity functions, shows that the suggested approach is effective for discriminating between topics that were strongly promoted by abusers and topics that attracted authentic public interest.

References

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  1. Measurement of Online Discussion Authenticity within Online Social Media

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          cover image ACM Conferences
          ASONAM '17: Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017
          July 2017
          698 pages
          ISBN:9781450349932
          DOI:10.1145/3110025

          Copyright © 2017 ACM

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          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 31 July 2017

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