A conceptual framework for community detection, characterisation and membership in a social internetworking scenario. (1st January 2014)

• Record Type: Journal Article
• Authors: De Meo, Pasquale; Nocera, Antonino; Quattrone, Giovanni; Ursino, Domenico
• Is Part Of: International journal of data mining, modelling and management. Volume 6:Number 1(2014)
• Page Start: 22
• Page End: 48
• Publication Date: 2014-01-01
• Subjects: social internetworking -- community characterisation -- community membership -- user similarity detection -- community detection; Data mining -- Periodicals; Information science -- Periodicals; Databases -- Periodicals; 005.7
• Languages: English
• ISSNs: 1759-1163

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.