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Towards Discovery of Influence and Personality Traits Through Social Link Prediction

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Authors
Nguyen, Thin
Phung, Dinh
Adams, Brett
Venkatesh, Svetha
Date
2011
Type
Conference Paper

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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.
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Proceedings of the Fifth International Conference on Weblogs and Social Media
Source Conference
ICWSM 2011 Fifth International Conference on Weblogs and Social Media
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Department of Computing
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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.