"On the internet, nobody knows you're a dog": A twitter case study of anonymity in social networks

Sai Teja Peddinti, Keith W. Ross, Justin Cappos

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

    Abstract

    Twitter does not impose a Real-Name policy for usernames, giving users the freedom to choose how they want to be identified. This results in some users being Identifiable (disclosing their full name) and some being Anonymous (disclosing neither their first nor last name). In this work we perform a large-scale analysis of Twitter to study the prevalence and behavior of Anonymous and Identifiable users. We employ Amazon Mechanical Turk (AMT) to classify Twitter users as Highly Identifiable, Identifiable, Partially Anonymous, and Anonymous. We find that a significant fraction of accounts are Anonymous or Partially Anonymous, demonstrating the importance of Anonymity in Twitter. We then select several broad topic categories that are widely considered sensitive-including pornography, escort services, sexual orientation, religious and racial hatred, online drugs, and guns-and find that there is a correlation between content sensitivity and a user's choice to be anonymous. Finally, we find that Anonymous users are generally less inhibited to be active participants, as they tweet more, lurk less, follow more accounts, and are more willing to expose their activity to the general public. To our knowledge, this is the first paper to conduct a large-scale data-driven analysis of user anonymity in online social networks.

    Original languageEnglish (US)
    Title of host publicationCOSN 2014 - Proceedings of the 2014 ACM Conference on Online Social Networks
    PublisherAssociation for Computing Machinery, Inc
    Pages83-93
    Number of pages11
    ISBN (Electronic)9781450331982
    DOIs
    StatePublished - Oct 1 2014
    Event2nd ACM Conference on Online Social Networks, COSN 2014 - Dublin, Ireland
    Duration: Oct 1 2014Oct 2 2014

    Publication series

    NameCOSN 2014 - Proceedings of the 2014 ACM Conference on Online Social Networks

    Other

    Other2nd ACM Conference on Online Social Networks, COSN 2014
    CountryIreland
    CityDublin
    Period10/1/1410/2/14

    Keywords

    • Anonymity
    • Behavioral analysis
    • Online social networks
    • Quantify
    • Twitter

    ASJC Scopus subject areas

    • Computer Networks and Communications

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  • Cite this

    Peddinti, S. T., Ross, K. W., & Cappos, J. (2014). "On the internet, nobody knows you're a dog": A twitter case study of anonymity in social networks. In COSN 2014 - Proceedings of the 2014 ACM Conference on Online Social Networks (pp. 83-93). (COSN 2014 - Proceedings of the 2014 ACM Conference on Online Social Networks). Association for Computing Machinery, Inc. https://doi.org/10.1145/2660460.2660467