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Analyzing Temporal Dynamics in Twitter Profiles for Personalized Recommendations in the Social Web

Abel, Fabian and Gao, Qi and Houben, Geert-Jan and Tao, Ke (2011) Analyzing Temporal Dynamics in Twitter Profiles for Personalized Recommendations in the Social Web. pp. 1-8. In: Proceedings of the ACM WebSci'11, June 14-17 2011, Koblenz, Germany.

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Official URL: http://www.websci11.org/fileadmin/websci/Papers/135_paper.pdf

Abstract

Social Web describes a new culture of participation on the Web where more and more people actively participate in publishing and organizing Web content. As part of this cul- ture, people leave a variety of traces when interacting with (other people via) Social Web systems. In this paper, we investigate user modeling strategies for inferring personal interest proles from Social Web interactions. In particular, we analyze individual micro-blogging activities on Twitter. We compare dierent strategies for creating user proles based on the Twitter messages a user has published and study how these proles change over time. Moreover, we evaluate the quality of the user modeling strategies in the context of personalized recommender systems and show that those strategies which consider the temporal dynamics of the individual proles allow for the best performance.

Item Type:Conference or Workshop Item (Paper)
Web Science Comments:WebSci Conference 2011
Subjects:WS9 Sociology > WS93 Social Networks
Web Science Events > Web Science 2011
ID Code:428
Deposited By: Lisa Sugiura
Deposited On:07 Jun 2011 16:53
Last Modified:25 Oct 2011 17:10

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