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Finding and Matching Communities in Social Networks Using Data Mining

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3 Author(s)
Slah Alsaleh ; Comput. Sci. Discipline, Queensland Univ. of Technol., Brisbane, QLD, Australia ; Richi Nayak ; Yue Xu

The rapid growth in the number of users using social networks and the information that a social network requires about their users make the traditional matching systems insufficiently adept at matching users within social networks. This paper introduces the use of clustering to form communities of users and, then, uses these communities to generate matches. Forming communities within a social network helps to reduce the number of users that the matching system needs to consider, and helps to overcome other problems from which social networks suffer, such as the absence of user activities' information about a new user. The proposed system has been evaluated on a dataset obtained from an online dating website. Empirical analysis shows that accuracy of the matching process is increased using the community information.

Published in:

Advances in Social Networks Analysis and Mining (ASONAM), 2011 International Conference on

Date of Conference:

25-27 July 2011