Homophilic network decomposition: a community-centric analysis of online social services

被引：3
作者：
Rossetti G. [1 ,2 ]
Pappalardo L. [2 ]
Kikas R. [3 ]
Pedreschi D. [2 ]
Giannotti F. [1 ]
Dumas M. [3 ]
机构：
[1] KDDLab, ISTI -CNR, Via G. Moruzzi, 1, Pisa
[2] KDDLab, University of Pisa, Largo B. Pontecorvo, 3, Pisa
[3] Unversity of Tartu, Tartu
来源：
Social Network Analysis and Mining | 2016年 / 6卷 / 1期
基金：
欧盟地平线“2020”;
关键词：
Online Social Network; Minority Class; Stochastic Gradient Descent; Community Detection Algorithm; User Engagement;
D O I：
10.1007/s13278-016-0411-4
中图分类号：
学科分类号：
摘要：
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+. © 2016, The Author(s).
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  • [1] Combining behavioral and social network data for online advertising, (2008)
  • [2] Bessi A., Petroni F., Vicario M.D., Zollo F., Anagnostopoulos A., Scala A., Caldarelli G., Quattrociocchi W., Viral misinformation: the role of homophily and polarization. In: Proceedings of the 24th international conference on world wide web companion, WWW 2015, Florence, Italy, May 18–22, 2015—companion volume, (2015)
  • [3] Bhatt R., Chaoji V., Parekh R., Predicting product adoption in large-scale social networks, In: CIKM, (2010)
  • [4] Blondel V.D., Guillaume J.L., Lambiotte R., Lefebvre E., Fast unfolding of communities in large networks, J Stat Mech Theory Exp, 2008, 10, (2008)
  • [5] Carullo G., Castiglione A., Santis A.D., Palmieri F., A triadic closure and homophily-based recommendation system for online social networks, World Wide Web 18(6), 1579-1601, Online, (2015)
  • [6] Clauset A., Newman MEJ, (2004)
  • [7] Coscia M., Giannotti F., Pedreschi D., A classification for community discovery methods in complex networks, In: CoRR, (2012)
  • [8] Coscia M., Rossetti G., Giannotti F., Pedreschi D., Uncovering hierarchical and overlapping communities with a local-first approach, In: TKDD, (2014)
  • [9] Domingos P., Richardson M., Mining the network value of customers, (2001)
  • [10] Elkabani I., Khachfeh R.A.A., Homophily-based link prediction in the facebook online social network: a rough sets approach, J Intell Syst 24(4), 491-503, Online, (2015)
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