Marginalization Effects in Face-to-face Social Networks

In a recent study featured in SIAM news Fariba Karimi, Marcos Oliveira, and Markus Strohmaier examine how the interplay between space and time constraints, together with group mixing and size imbalance, can produce structural marginalization in face-to-face interactions. They used computational models of face-to-face interactions to consider the heterogeneity in individuals’ characteristics (e.g., race, gender, and ethnicity) and group mixing biases that establish the probability of interactions within groups. Their analysis shows that the majority group’s mixing accounts for most of the variance in connectivity inequality, and that the minority group alone can only slightly reduce inequality.

They also identified a tipping point that determines the way in which minorities should strategize their social interactions. When the minority group size is below a critical point, homophilic minority interaction decreases minority connectivity. Conversely, homophilic minority interaction helps increase minority connectivity when the minority group size is sufficiently large. Their findings suggest that structural marginalization is challenging to mitigate without the help of the majority group, and that additional computational network-theoretic research is necessary to shed light on this form of marginalization and the possible mitigation of its effects.

Image by Freepik

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