Conformity a Path-Aware Homophily measure for Node-Attributed Networks

Unveil the homophilic/heterophilic behaviors that characterize the wiring patterns of complex networks is an important task in social network analysis, often approached studying the assortative mixing of node attributes. Recent works underlined that a global measure to quantify node homophily necessarily provides a partial, often deceiving, picture of the reality. Moving from such literature, in this work, we propose a novel measure, namely Conformity, designed to overcome such limitation by providing a node-centric quantification of assortative mixing patterns. Differently from the measures proposed so far, Conformity is designed to be path-aware, thus allowing for a more detailed evaluation of the impact that nodes at different degrees of separations have on the homophilic embeddedness of a target. Experimental analysis on synthetic and real data allowed us to observe that Conformity can unveil valuable insights from node-attributed graphs.

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Additional Info
Field Value
Author Rossetti, Giulio
Author Citraro, Salvatore
Author Milli, Letizia
DOI 10.1109/MIS.2021.3051291
Group Select Group
Publisher IEEE Intelligent Systems
Source IEEE Intelligent Systems 13 January 2021 Page 1-1
Thematic Cluster Social Network Analysis [SNA]
system:type JournalArticle
Management Info
Field Value
Author Wright Joanna
Maintainer Giulio Rossetti
Version 1
Last Updated 5 March 2021, 12:33 (CET)
Created 4 February 2021, 14:01 (CET)