A multiplex network approach to farmers’ friendship relationships: a case study from rural Ghana

Abstract This study applies a multiplex network framework to analyze farmers’ friendship relationships in Kunsum Camp, a rural Ghanaian community, using primary data from 45 farming households. By modeling six relationship layers categorized by farming/non-farming and reciprocal, directional, or intimate ties—we uncover structural properties and interlayer dynamics driving knowledge diffusion. We introduce the Interlayer Influence Score (IIS), a novel metric integrating degree centrality and edge overlap, to identify multifunctional hubs. Simulations of knowledge diffusion validate IIS’s predictive power for innovation adoption. The farming-related directional layer (FADIR) exhibits the highest density (0.073) and centralization (0.236), with limited interlayer overlap $ (\leq 7%) $ indicating distinct social roles. While constrained by a single-case design, this study extends multiplex network methodologies by incorporating dynamic modeling and offers a replicable framework for small-scale agricultural networks, with implications for targeted extension programs.

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Publication Details

Journal
Journal of Complex Networks
Published
2025-09-29
DOI
https://doi.org/10.1093/comnet/cnaf039
Primary Topic
Agricultural Innovations and Practices
Type
article
Field-Weighted Citation Impact
0.00
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article

A multiplex network approach to farmers’ friendship relationships: a case study from rural Ghana

Patience Pokuaa Gambrah, Marcial Nguemfouo
Journal of Complex Networks
Agricultural Innovations and Practices
article

A multiplex network approach to farmers’ friendship relationships: a case study from rural Ghana

Patience Pokuaa Gambrah, Marcial Nguemfouo
article en

Abstract

Abstract This study applies a multiplex network framework to analyze farmers’ friendship relationships in Kunsum Camp, a rural Ghanaian community, using primary data from 45 farming households. By modeling six relationship layers categorized by farming/non-farming and reciprocal, directional, or intimate ties—we uncover structural properties and interlayer dynamics driving knowledge diffusion. We introduce the Interlayer Influence Score (IIS), a novel metric integrating degree centrality and edge overlap, to identify multifunctional hubs. Simulations of knowledge diffusion validate IIS’s predictive power for innovation adoption. The farming-related directional layer (FADIR) exhibits the highest density (0.073) and centralization (0.236), with limited interlayer overlap $ (\leq 7%) $ indicating distinct social roles. While constrained by a single-case design, this study extends multiplex network methodologies by incorporating dynamic modeling and offers a replicable framework for small-scale agricultural networks, with implications for targeted extension programs.

Journal of Complex NetworksVol. 13(6)
Université de Yaoundé I (CM), Kumasi Technical University (GH)
Openalex Percentile: Top 52%
Agricultural Innovations and Practices
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A multiplex network approach to farmers’ friendship relationships: a case study from rural Ghana — Patience Pokuaa Gambrah, Marcial Nguemfouo · Journal of Complex Networks (2025) | TGRS Research Map | TGRS