Articolo in rivista, 2016, ENG, 10.1007/s13278-016-0411-4
Rossetti G.; Pappalardo L.; Kikas R.; Pedreschi D.; Giannotti F.; Dumas M.
Department of Computer Science, University of Pisa, Pisa - CNR-ISTI, Pisa, Italy; Department of Computer Science, University of Pisa, Pisa - CNR-ISTI, Pisa, Italy; University of Tartu, Tartu, Estonia; University of Pisa, Pisa, Italy; CNR-ISTI, Pisa, Italy; University of Tartu, Tartu, Estonia
In this paper we formulate the homophilic network decomposition problem: Is it possible to identify a network partition whose structure is able to characterize the degree of homophily of its nodes? The aim of our work is to understand the relations between the homophily of individuals and the topological features expressed by specific network substructures. We apply several community detection algorithms on three large-scale online social networks--Skype, LastFM and Google+--and advocate the need of identifying the right algorithm for each specific network in order to extract a homophilic network decomposition. Our results show clear relations between the topological features of communities and the degree of homophily of their nodes in three online social scenarios: product engagement in the Skype network, number of listened songs on LastFM and homogeneous level of education among users of Google+.
Social Network Analysis and Mining 6 (1)
Complex Networks, Community Discovery, Classification
Rossetti Giulio, Pappalardo Luca, Giannotti Fosca
ISTI – Istituto di scienza e tecnologie dell'informazione "Alessandro Faedo"
ID: 366891
Year: 2016
Type: Articolo in rivista
Creation: 2017-02-13 11:25:33.000
Last update: 2021-01-25 18:24:00.000
External links
OAI-PMH: Dublin Core
OAI-PMH: Mods
OAI-PMH: RDF
DOI: 10.1007/s13278-016-0411-4
URL: https://link.springer.com/article/10.1007/s13278-016-0411-4
External IDs
CNR OAI-PMH: oai:it.cnr:prodotti:366891
DOI: 10.1007/s13278-016-0411-4
Scopus: 2-s2.0-84993929502
ISI Web of Science (WOS): 000394219100013