An Application of Community Discovery in Academical Social Networks

Arslan E., Akyokus S., Ganiz M. C.

IEEE International Symposium on INnovations in Intelligent SysTems and Applications (INISTA), Bulgaristan, 19 - 21 Haziran 2013 identifier identifier


The objective of this study is to discover social communities in a social network using different social network community discovery methods that utilize metrics and structures like degree, clustering coefficient, k-cores, weak and strong components. We have used two different datasets and methods: K-core community discovery method for DBLP dataset and Main Path Analysis method for Arxiv High-energy physics theory citation network. At the end of the analyses, we have obtained several reports that represent the skeleton structure of the communities in the networks.