Simulate to Detect: A Multi-agent System for Community Detection
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 02
Imagined communities: awareness, information sharing, and privacy on the facebook
PET'06 Proceedings of the 6th international conference on Privacy Enhancing Technologies
A Community Based Algorithm for Deriving Users' Profiles from Egocentrics Networks
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
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In most online social networks, with the increasing number of users and content, the problem of contact filtering becomes more and more present. The recent introduction of such features in online social networks -- for instance, Circles in Google+ or Facebook Smart lists -- shows that it is a problem they are confronted to. In this paper, we explore this question through multidisciplinary aspects. First, we discuss about this issue of groups management in the context of social networks. Then, we present several techniques from the state of the art to automatically find meaningful groups of contacts in a user's contact list. Finally, we asked Facebook users to evaluate these solutions on their own Facebook network, both to compare the solutions among themselves and to assess how pertinent the best ones are according to them. The conclusions of this study is that a network analysis approach can strongly improve the efficiency of an automated detection of groups on networks, which could be used, combined with profile data extraction, to design intelligent management of groups of contacts.