NDLI: Circle based community detection

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Content Provider	ACM Digital Library
Author	Narayanam, Ramasuri Lamba, Hemank
Abstract	The connection patterns among individuals or objects in complex (social) networks possess rich information that can be useful for conducting effecient network analysis. In particular we consider the task of community detection in social networks. Nowadays social networking sites allow users to categorize their friends into different lists. Some of the examples being 'circles' on Google +, 'lists' on Twitter and Facebook. This information captures the reason of friendship between two users. In this paper we explore how this information can lead to detecting better community structures. We pose this task as a community detection problem where the algorithm does not have the information about the underlying edges. Experiments are conducted on 3 real world social networks - Google +, Twitter and Facebook. The experiment shows that results obtained are better than the results obtained by community detection over the original graph.
Starting Page	1
Ending Page	4
Page Count	4
File Format	PDF
ISBN	9781450323208
DOI	10.1145/2528228.2528245
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2013-10-17
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Community detection Social networks
Content Type	Text
Resource Type	Article

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Circle based community detection