Relation and Attribute Fusion to Detect Communities of Online Social Networks

MEHRAFARIN, ADAMI and MOHAMMAD H., NADIMI-SHAHRAKI (2015) Relation and Attribute Fusion to Detect Communities of Online Social Networks. In: International Conference on Advances in Computing, Control and Networking - ACCN 2015, 21 - 22 February 2015, Hotel Lebua at State Tower.

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Abstract

Community detection is a vital research area for online social networks. Since there is not a formal context in users` profiles, a new data source of user`s attributes is extracted from online social networks. Then in this paper a novel algorithm is investigated. Both attributes and relations of users are used in the proposed algorithm; therefor e communities can be detected through users’ similar characteristics or users common relationships. The experiments show that the accuracy of the algorithm is comparable to other well-known algorithms; moreover detected communities are self-descripted through the mode of each community members.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Social networks, Community detection, Influential nodes, Self-descriptive communities
Depositing User: Mr. John Steve
Date Deposited: 09 May 2019 11:07
Last Modified: 09 May 2019 11:07
URI: http://publications.theired.org/id/eprint/2099

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