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Towards discovery of influence and personality traits through social link prediction
conference contribution
posted on 2011-01-01, 00:00 authored by Thin NguyenThin Nguyen, Quoc-Dinh Phung, B Adams, Svetha VenkateshSvetha VenkateshEstimation 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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Event
International Conference on Weblogs and Social Media (5th : 2011 : Barcelona, Spain)Pagination
566 - 569Publisher
AAAI PressLocation
Barcelona, SpainPlace of publication
Menlo Park, Calif.Start date
2011-07-17End date
2011-07-21Language
engPublication classification
E1.1 Full written paper - refereedCopyright notice
2011, Association for the Advancement of Artificial IntelligenceTitle of proceedings
ICWSM-11 : Proceedings of the 5th AAAI International Conference on Weblogs and Social MediaUsage metrics
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