Based on an expert systems approach, the issue of community detection can be conceptualized as a clustering model for networks. Building upon this further, community structure can be measured through a clustering coefficient, which is generated from the number of existing triangles around the nodes over the number of triangles that can be hypothetically constructed. This paper provides a new definition of the clustering coefficient for weighted networks under a generalized definition of triangles. Specifically, a novel concept of triangles is introduced, based on the assumption that, should the aggregate weight of two arcs be strong enough, a link between the uncommon nodes can be induced. Beyond the intuitive meaning of such generalized triangles in the social context, we also explore the usefulness of them for gaining insights into the topological structure of the underlying network. Empirical experiments on the standard networks of 500 commercial US airports and on the nervous system of the Caenorhabditis elegans support the theoretical framework and allow a comparison between our proposal and the standard definition of clustering coefficient.

Cerqueti, R., Ferraro, G., Iovanella, A. (2018). A new measure for community structures through indirect social connections. EXPERT SYSTEMS WITH APPLICATIONS, 114, 196-209 [10.1016/j.eswa.2018.07.040].

A new measure for community structures through indirect social connections.

Ferraro, Giovanna;Iovanella, Antonio
2018-12-30

Abstract

Based on an expert systems approach, the issue of community detection can be conceptualized as a clustering model for networks. Building upon this further, community structure can be measured through a clustering coefficient, which is generated from the number of existing triangles around the nodes over the number of triangles that can be hypothetically constructed. This paper provides a new definition of the clustering coefficient for weighted networks under a generalized definition of triangles. Specifically, a novel concept of triangles is introduced, based on the assumption that, should the aggregate weight of two arcs be strong enough, a link between the uncommon nodes can be induced. Beyond the intuitive meaning of such generalized triangles in the social context, we also explore the usefulness of them for gaining insights into the topological structure of the underlying network. Empirical experiments on the standard networks of 500 commercial US airports and on the nervous system of the Caenorhabditis elegans support the theoretical framework and allow a comparison between our proposal and the standard definition of clustering coefficient.
Pubblicato
Rilevanza internazionale
Articolo
Esperti anonimi
Settore ING-IND/35 - Ingegneria Economico-Gestionale
Settore SECS-S/06 - Metodi mat. dell'economia e Scienze Attuariali e Finanziarie
English
Con Impact Factor ISI
complex networks
local cohesiveness
clustering coefficient
generalized triangles
https://www.sciencedirect.com/science/article/pii/S0957417418304639
Cerqueti, R., Ferraro, G., Iovanella, A. (2018). A new measure for community structures through indirect social connections. EXPERT SYSTEMS WITH APPLICATIONS, 114, 196-209 [10.1016/j.eswa.2018.07.040].
Cerqueti, R; Ferraro, G; Iovanella, A
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/201439
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