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    Towards Discovery of Influence and Personality Traits Through Social Link Prediction

    Access Status
    Fulltext not available
    Authors
    Nguyen, Thin
    Phung, Dinh
    Adams, Brett
    Venkatesh, Svetha
    Date
    2011
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Nguyen, T. and Phung, D. and Adams, B. and Venkatesh, S. 2011. Towards Discovery of Influence and Personality Traits Through Social Link Prediction, in Nicolov, N. and Shanahan, J. (ed), Proceedings of the Fifth International Conference on Weblogs and Social Media (ICWSM), Jul 17 2011, pp. 566-569. Barcelona, Spain: IAAA.
    Source Title
    Proceedings of the Fifth International Conference on Weblogs and Social Media
    Source Conference
    ICWSM 2011 Fifth International Conference on Weblogs and Social Media
    Additional URLs
    http://www.aaai.org/ocs/index.php/ICWSM/ICWSM11/paper/view/2772
    ISBN
    9781577355052
    School
    Department of Computing
    URI
    http://hdl.handle.net/20.500.11937/21742
    Collection
    • Curtin Research Publications
    Abstract

    Estimation of a person's influence and personality traits from social media data has many applications. We use social linkage criteria, such as number of followers and friends, as proxies to form corpora, from popular blogging site Livejournal, for examining two two-class classification problems: influential vs. non-influential, and extraversion vs. introversion. Classification is performed using automatically-derived psycholinguistic and mood-based features of a user's textual messages. We experiment with three sub-corpora of 10000 users each, and present the most effective predictors for each category. The best classification result, at 80%, is achieved using psycholinguistic features; e.g., influentials are found to use more complex language, than non-influentials, and use more leisure-related terms.

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