FRec: a novel framework of recommending users and communities in social media

Authors:
Lei Li;Wei Peng;Saurabh Kataria;Tong Sun;Tao Li
Affiliations:
Florida International University, Miami, FL, USA;Xerox Corporation, Webster, NY, USA;Xerox Corporation, Webster, NY, USA;Xerox Corporation, Webster, NY, USA;Florida International University, Miami, FL, USA
Venue:
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Year:
2013

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Abstract

In this paper, we propose a framework of recommending users and communities in social media. Given a user's profile, our framework is capable of recommending influential users and topic-cohesive interactive communities that are most relevant to the given user. In our framework, we present a generative topic model to discover user-oriented and community-oriented topics simultaneously, which enables us to capture the exact topic interests of users, as well as the focuses of communities. Extensive evaluation on a data set obtained from Twitter has demonstrated the effectiveness of our proposed framework compared with other probabilistic topic model based recommendation methods.