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Homophilic organization of egocentric communities in ICT services
Homophilic organization of egocentric communities in ICT services
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Homophilic organization of egocentric communities in ICT services
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Homophilic organization of egocentric communities in ICT services
Homophilic organization of egocentric communities in ICT services

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Homophilic organization of egocentric communities in ICT services
Homophilic organization of egocentric communities in ICT services
Journal Article

Homophilic organization of egocentric communities in ICT services

2025
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Overview
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 studied mainly in the context of link formation and social dynamics. However, less is known about the role of the multidimensional homophily in forming egocentric communities on Information and Communications Technology (ICT) services. To close this gap, we analyze three ICT datasets, namely, two online social networks and one network deduced from mobile phone calls, in all of which data about individual features are available. We identify communities within egocentric networks and surprisingly find that the larger the community, 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 maintaining a large diverse group may exceed the capacity of the members. As the ego reaches out to their 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 their alters displays a non-monotonic behavior 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 the empirical observations and shows the reason behind non-monotonic tendency of the egocentric feature overlap as a function of the ego’s degree.