Bridging material culture networks and social networks in archaeology

This study examines whether material culture can serve as a proxy for past social interaction. Using the ArchMatNet agent-based model, we simulate social behavior in small-scale communities and resulting material culture production, then compare social and material culture networks. We compare networks using graph correlation and the quadratic assignment procedure, evaluate parameter effects with generalized additive models, and assess underlying structures with exponential random graph models. Within this simulated system, results show strong correlations between social interaction networks and material culture networks, especially when material culture traits are sufficiently variable. However, correlations weaken under some conditions, particularly low material culture variation, indicating limits to archaeological network inference. Key factors include interaction frequency, learning strategy, and trait visibility. These results characterize hypothetical relationships generated under the model's assumptions; they do not constitute empirical validation. They highlight both the promise and the constraints of using material culture as a proxy for social networks and underscore the need for empirical testing and careful attention to network structure.

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Publication Details

Journal
PLoS ONE
Published
2026-10-16
DOI
https://doi.org/10.1371/journal.pone.0358860
Primary Topic
Language and cultural evolution
Type
article
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article

Bridging material culture networks and social networks in archaeology

Cecilia Padilla‐Iglesias, Robert Bischoff
PLoS ONE
Language and cultural evolution
article

Bridging material culture networks and social networks in archaeology

Cecilia Padilla‐Iglesias, Robert Bischoff
article en

Abstract

This study examines whether material culture can serve as a proxy for past social interaction. Using the ArchMatNet agent-based model, we simulate social behavior in small-scale communities and resulting material culture production, then compare social and material culture networks. We compare networks using graph correlation and the quadratic assignment procedure, evaluate parameter effects with generalized additive models, and assess underlying structures with exponential random graph models. Within this simulated system, results show strong correlations between social interaction networks and material culture networks, especially when material culture traits are sufficiently variable. However, correlations weaken under some conditions, particularly low material culture variation, indicating limits to archaeological network inference. Key factors include interaction frequency, learning strategy, and trait visibility. These results characterize hypothetical relationships generated under the model's assumptions; they do not constitute empirical validation. They highlight both the promise and the constraints of using material culture as a proxy for social networks and underscore the need for empirical testing and careful attention to network structure.

PLoS ONEVol. 21(10)
Arizona State University (US), University of Tübingen (DE)
Openalex Percentile: Top 3%
Language and cultural evolution
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