Title: A conceptual framework for community detection, characterisation and membership in a social internetworking scenario

Authors: Pasquale De Meo; Antonino Nocera; Giovanni Quattrone; Domenico Ursino

Addresses: Dipartimento di Fisica, Sezione di Informatica, Universitá di Messina, Viale F. Stagno D'Alcontres, 31, 98166 Messina, Italy ' DIMET, Universitá Mediterranea di Reggio Calabria, Via Graziella, Localitá Feo di Vito, 89122 Reggio Calabria, Italy ' Department of Computer Science, University College of London, Malet Place Engineering Building, London, WC1E 6BT, UK ' DIMET, Universitá Mediterranea di Reggio Calabria, Via Graziella, Localitá Feo di Vito, 89122 Reggio Calabria, Italy

Abstract: Social internetworking systems are becoming a challenging new reality; they group together multiple, and possibly heterogenous, social networks. The typical problems of social network research become much more complex in a social internetworking context. In this paper, we propose a conceptual framework, and an underlying model, to handle some of these problems, namely community detection, characterisation and membership in a social internetworking scenario. In order to face them, we must preliminarily investigate a further problem, i.e., user similarity detection.

Keywords: social internetworking; community characterisation; community membership; user similarity detection; community detection; social networks.

DOI: 10.1504/IJDMMM.2014.059980

International Journal of Data Mining, Modelling and Management, 2014 Vol.6 No.1, pp.22 - 48

Available online: 23 Mar 2014 *

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