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Towards discovery of influence and personality traits through social link prediction

Nguyen, Thin, Phung, Dinh, Adams, Brett and Venkatesh, Svetha 2011, Towards discovery of influence and personality traits through social link prediction, in ICWSM-11 : Proceedings of the 5th AAAI International Conference on Weblogs and Social Media, AAAI Press, Menlo Park, Calif., pp. 566-569.

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Title Towards discovery of influence and personality traits through social link prediction
Author(s) Nguyen, ThinORCID iD for Nguyen, Thin orcid.org/0000-0003-3467-8963
Phung, DinhORCID iD for Phung, Dinh orcid.org/0000-0002-9977-8247
Adams, Brett
Venkatesh, SvethaORCID iD for Venkatesh, Svetha orcid.org/0000-0001-8675-6631
Conference name International Conference on Weblogs and Social Media (5th : 2011 : Barcelona, Spain)
Conference location Barcelona, Spain
Conference dates 17-21 Jul. 2011
Title of proceedings ICWSM-11 : Proceedings of the 5th AAAI International Conference on Weblogs and Social Media
Editor(s) [Unknown]
Publication date 2011
Conference series International Conference on Weblogs and Social Media
Start page 566
End page 569
Total pages 4
Publisher AAAI Press
Place of publication Menlo Park, Calif.
Keyword(s) social media
users
blogging
influence
personality traits
followers
friends
Livejournal
Summary 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.
Language eng
Field of Research 089999 Information and Computing Sciences not elsewhere classified
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1.1 Full written paper - refereed
Copyright notice ©2011, Association for the Advancement of Artificial Intelligence
Persistent URL http://hdl.handle.net/10536/DRO/DU:30044828

Document type: Conference Paper
Collection: School of Information Technology
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