A Classification for Community Discovery Methods in Complex Networks

Day - Time: 10 June 2013, h.11:00
Place: Area della Ricerca CNR di Pisa - Room: C-29

Andrea Esuli


In the last few years many real-world networks have been found to show a so-called community structure organization. Much effort has been devoted in the literature to develop methods and algorithms that can efficiently highlight this hidden structure of the network, traditionally by partitioning the graph. Since network representation can be very complex and can contain different variants in the traditional graph model, each algorithm in the literature focuses on some of these properties and establishes, explicitly or implicitly, its own definition of community. According to this definition it then extracts the communities that are able to reflect only some of the features of real communities. The aim of this survey is to provide a manual for the community discovery problem. Given a meta definition of what a community in a social network is, our aim is to organize the main categories of community discovery based on their own definition of community. Given a desired definition of community and the features of a problem (size of network, direction of edges, multidimensionality, and so on) this review paper is designed to provide a set of approaches that researchers could focus on.

NOTE: This seminar is the sixth one of the series of six seminars presented by the winners of the prize "Young researchers ISTI 2013". Michele Coscia placed second in the Young Researcher category.