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. Attached Files Name Description MIMEType Size Downloads Title Towards discovery of influence and personality traits through social link prediction Author(s) Nguyen, Thin orcid.org/0000-0003-3467-8963 Phung, Dinh orcid.org/0000-0002-9977-8247 Adams, Brett 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 Related Links Link Description Connect to published version Go to link with your DU access privileges     Link to Related Work Towards discovery of influence and personality traits through social link prediction (deposited 09-10-2017) AAAI Press Publisher (deposited 06-11-2013) Association for the Advancement of Artificial Intelligence (AAAI) Publisher (deposited 08-05-2012)   Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Tue, 01 May 2012, 11:00:52 EST Fri, 04 May 2012, 12:23:38 EST Fri, 04 May 2012, 12:28:04 EST Mon, 14 May 2012, 10:05:43 EST Wed, 15 Jan 2014, 12:59:19 EST Tue, 28 Jan 2014, 14:40:42 EST Wed, 06 Aug 2014, 15:56:25 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 0 times in Scopus Search Google Scholar Access Statistics: 310 Abstract Views, 2 File Downloads  -  Detailed Statistics Created: Tue, 01 May 2012, 11:00:52 EST

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