Homophilic organization of egocentric communities in ICT services

TL;DR

This study investigates how homophily influences community formation in ICT-based egocentric networks, revealing that larger communities tend to have more feature overlap and proposing a mechanism explaining these patterns.

Contribution

It introduces a comprehensive analysis of multiple ICT datasets to uncover the role of feature similarity in community size and structure, and proposes a model for link addition in egocentric networks.

Findings

Larger communities exhibit more feature overlap among members.

The first community member tends to have higher feature overlap with the ego.

Feature overlap with alters shows non-monotonic behavior as ego's degree increases.

Abstract

Members of a society can be characterized by a large number of features, such as gender, age, ethnicity, religion, social status, and shared activities. One of the main tie-forming factors between individuals in human societies is homophily, the tendency of being attracted to similar others. Homophily has been mainly studied with focus on one of the features and little is known about the roles of similarities of different origins in the formation of communities. To close this gap, we analyze three datasets from Information and Communications Technology (ICT) services, namely, two online social networks and a network deduced from mobile phone calls, in all of which metadata about individual features are available. We identify communities within egocentric networks and surprisingly find that the larger the community is, the more overlap is found between features of its members and the ego. We interpret this finding in terms of the effort needed to manage the communities; the larger diversity requires more effort such that to maintain a large diverse group may exceed the capacity of the members. As the ego reaches out to her alters on an ICT service, we observe that the first alter in each community tends to have a higher feature overlap with the ego than the rest. Moreover the feature overlap of the ego with all her alters displays a non-monotonic behaviors as a function of the ego's degree. We propose a simple mechanism of how people add links in their egocentric networks of alters that reproduces all the empirical observations and shows the reason behind non-monotonic tendency of the egocentric feature overlap as a function of the ego's degree.