Deep description of static and dynamic network ties in Honduran villages

TL;DR

This study analyzes how personal attributes and community factors influence the formation and evolution of various social networks in Honduran villages over time, revealing patterns of assortativity and the impact of socio-economic changes.

Contribution

It provides a detailed longitudinal analysis of multiplex social networks in rural Honduras, highlighting how individual and community attributes shape network dynamics and structure.

Findings

Gender and religion significantly influence network assortativity.

Educational and financial factors increasingly affect social ties over time.

Networks show distinct patterns of cooperation and conflict based on personal attributes.

Abstract

We examine static and dynamic social network structure in 176 villages within the Copan Department of Honduras across two data waves (2016, 2019), using detailed data on multiplex networks for 20,232 individuals enrolled in a longitudinal survey. These networks capture friendship, health advice, financial help, and adversarial relationships, allowing us to show how cooperation and conflict jointly shape social structure. Using node-level network measures derived from near-census sociocentric village networks, we leverage mixed-effects zero-inflated negative binomial models to assess the influence of individual attributes, such as gender, marital status, education, religion, and indigenous status, and of village characteristics, on the dynamics of social networks over time. We complement these node-level models with dyadic assortativity (odds-ratio-based homophily) and community-level measures to describe how sorting by key attributes differs across network types and between waves. Our results demonstrate significant assortativity based on gender and religion, particularly within health and financial networks. Across networks, gender and religion exhibit the most consistent assortative mixing. Additionally, community-level assortativity metrics indicate that educational and financial factors increasingly influence social ties over time. Our findings provide insights into how personal attributes and community dynamics interact to shape network formation and socio-economic relationships in rural settings over time.