A SURVEY OF COMMUNITY DETECTION IN ONLINE SOCIAL NETWORK

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dc.contributor.authorPadma Priya B
dc.contributor.authorSathiyakumari K
dc.date.accessioned2020-12-24T05:12:23Z
dc.date.available2020-12-24T05:12:23Z
dc.date.issued2013-07
dc.description.abstractIn this paper we present a large Scale Community detection and analysis of Facebook, which gathers more than one billion active users in 2012. Characteristics of this online social network have been widely researched over these years. Facebook has affected the social life and activity of people in various ways. One major fact in today's technical world, people are very active users of Online Social Networks. They share every details of their day to day life and are in touch with their loved ones no matter in which part of the world they live. The impact is considerably taken into account as this online Social Network play a very important role in people lives. We study the structural properties of these samples in order to discover their community Structure. Here two Clustering algorithms are used to discover the communities in Complex networks and is compared.en_US
dc.identifier.issn2277-9655
dc.identifier.urihttp://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.404.1633&rep=rep1&type=pdf
dc.identifier.urihttps://dspace.psgrkcw.com/handle/123456789/2374
dc.language.isoenen_US
dc.publisherInternational Journal of Engineering Sciences & Research Technologyen_US
dc.subjectData miningen_US
dc.subjectComplex Networksen_US
dc.subjectCommunity Miningen_US
dc.subjectCommunity Detectionen_US
dc.titleA SURVEY OF COMMUNITY DETECTION IN ONLINE SOCIAL NETWORKen_US
dc.typeArticleen_US

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