Finding sensitive accounts on Twitter: An automated approach based on follower anonymity

Sai Teja Peddinti, Keith W. Ross, Justin Cappos

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

    Abstract

    We explore the feasibility of automatically finding accounts that publish sensitive content on Twitter, by examining the percentage of anonymous and identifiable followers the accounts have. We first designed a machine learning classifier to automatically determine if a Twitter account is anonymous or identifiable. We then classified an account as potentially sensitive based on the percentages of anonymous and identifiable followers the account has. We applied our approach to approximately 100,000 accounts with 404 million active followers. The approach uncovered accounts that were sensitive for a diverse number of reasons.

    Original languageEnglish (US)
    Title of host publicationProceedings of the 10th International Conference on Web and Social Media, ICWSM 2016
    PublisherAAAI press
    Pages655-658
    Number of pages4
    ISBN (Electronic)9781577357582
    StatePublished - Jan 1 2016
    Event10th International Conference on Web and Social Media, ICWSM 2016 - Cologne, Germany
    Duration: May 17 2016May 20 2016

    Publication series

    NameProceedings of the 10th International Conference on Web and Social Media, ICWSM 2016

    Other

    Other10th International Conference on Web and Social Media, ICWSM 2016
    CountryGermany
    CityCologne
    Period5/17/165/20/16

    ASJC Scopus subject areas

    • Computer Networks and Communications

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  • Cite this

    Peddinti, S. T., Ross, K. W., & Cappos, J. (2016). Finding sensitive accounts on Twitter: An automated approach based on follower anonymity. In Proceedings of the 10th International Conference on Web and Social Media, ICWSM 2016 (pp. 655-658). (Proceedings of the 10th International Conference on Web and Social Media, ICWSM 2016). AAAI press.