NDLI: A clique-superposition model for social networks

Content Provider	Springer Nature Link
Author	Yan, Fei Cai, ShaoWei Zhang, Ming Liu, GuoJun Deng, ZhiHong
Copyright Year	2012
Abstract	How does a social network evolve? Sociologists have studied this question for many years. According to some famous sociologists, social links are driven by social intersections. Actors who affiliate with the shared intersections tend to become interpersonally linked and form a cluster. In the social network, an actor cluster could be a clique or a group of several smaller-sized cliques. Thus we can conclude that a social network is composed of superposed cliques of different sizes. However, sociologists did not verify the theory in large scale data due to lack of computing ability. Motivated by this challenge, incorporated with the theory, we utilize data mining technologies to study the evolution patterns of large scale social networks in real world. Then, we propose a novel Clique-superposition generative model, which generates undirected weighted networks. By extensive experiments, we demonstrate that our model can generate networks with static and time evolving patterns observed not only in earlier literature but also in our work.
Starting Page	1
Ending Page	19
Page Count	19
File Format	PDF
ISSN	1674733X
Journal	Science in China Series : Information Sciences
Volume Number	56
Issue Number	5
e-ISSN	18691919
Language	English
Publisher	SP Science China Press
Publisher Date	2012-04-11
Publisher Place	Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	social networks graph mining Clique-superposition graph generator KEWLS Information Systems and Communication Service
Content Type	Text
Resource Type	Article
Subject	Computer Science

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