Bridging Material Culture Networks and Social Networks in Archaeology

  1. Robert J Bischoff
  2. Cecilia Padilla-Iglesias

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Abstract

This study investigates how different types of social interactions are reflected in the archaeological record, specifically analyzing the extent to which artifacts can serve as proxies for past human interactions. Utilizing the ArchMatNet agent-based model (ABM), we simulate the social behaviors of small-scale communities and their material culture production, enabling a comparative analysis of social and material culture networks. The networks were compared using graph correlation and the quadratic assignment procedure (QAP), the effects of model parameters on correlation strength were analyzed using generalized additive models (GAMs), and underlying network structures were compared using Exponential Random Graph Models (ERGMs). Our results demonstrate strong correlations between social interaction networks and material culture networks, particularly when significant variation is present in material culture traits. The study also demonstrates that some circumstances, such as low material culture variation, can present poor correlations. Thus, there is some caution for the application of network methods to archaeological data. Key factors influencing these correlations include the frequency of interaction, learning strategies, and the visibility of cultural traits. The study underscores the complexity of using material culture as a proxy for social networks, emphasizing the importance of empirical validation and careful consideration of network structures. The findings highlight the potential of ABMs as a methodological tool in archaeology to explore and validate methodological tools.

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  1. Version published to 10.31235/osf.io/wjsyg_v5 on OSF Preprints
  2. Version published to 10.31235/osf.io/wjsyg_v4 on OSF Preprints
  3. Peer Community in Archaeology

    This paper proceeds from a very important question, one that remains under-theorized in network approaches in archaeology: to what extent do patterns in material culture (especially material culture similarity) reflect underlying social interactions? The authors situate this question within a growing body of network science scholarship in which similarity based material culture networks are used as proxies for past social connectivity. Although relational thinking has increasingly been mobilized to move beyond rigid culture-historical categories, the connection between artifact similarity and social interaction is often treated as self-evident rather than explicitly examined. In this paper, the authors aim to evaluate how similarity networks might approximate interaction networks, and in so doing, clarify where and why this similarity is less evident. I was particularly interested in the central question of whether similarity in material culture can reflect underlying social networks, and if so, under what conditions. This is a foundational issue for archaeological network research. If similarity in material culture does not directly reflect past social interaction but instead results from differences in how material culture was made and used, then we need clearer theoretical and methodological criteria for assessing when similarity can be interpreted as evidence of social connectivity and when it cannot (see Gheorghiade et al. forthcoming).

    In this paper, Bischoff and Padilla-Iglesias rely on an agent-based model (ABM) (ArchMatNet) originally designed to replicate simple social interaction among hunter-gatherers, to explore how material culture networks and social interaction networks correlate. Their analysis draws on more than 30,000 simulations to produce two different types of networks: social interaction networks based on visiting, trading, and learning; and material culture networks where similarity is constructed from ceramic and point assemblages. Similarity in the latter is calculated using a weighted Jaccard index. The resulting networks are compared using three additional methods: graph correlation, quadratic assignment procedure (QAP), and Exponential Random Graph Models (ERGMs). This multi-method strategy moves the discussion beyond abstract debate toward experimentally grounded inference. By including ERGMs the authors can also assess whether the resulting networks share similar generative structures, rather than only measuring correlation. The results show that material culture networks more closely resemble interaction networks when variation in assemblages is sufficiently high, but that this correspondence weakens with lower variability, extended time depth, or with uneven transmission patterns.

    Taken together, the results in this paper point to three main conclusions. First, material culture networks can provide good representations of interaction networks when sufficient variation exists in the assemblages, particularly when camps begin with distinct traits (the uniqueTraits parameter). Second, material culture networks were inherently “fuzzier” than interaction networks. For example, the relationship between them was not as strong as those between different types of social networks. Third, different types of material culture (e.g., pots and points) could produce different results and network structures. This led the authors to suggest that combining multiple categories of material culture might provide a more accurate representation of interaction patterns. I particularly appreciated the authors' experimental approach to isolating the conditions under which material culture can function as a proxy for social interaction. By combining the ABM with multiple other network comparison methods, this paper tests, in a systematic way, when material similarity networks correspond to interaction patterns.

    The peer-review process further improved the clarity of the manuscript. Some of the suggestion submitted by reviewers included: clarifications on the QAP procedure, further discussion of the application of the ERGM and its implications for analysis, and further reflection on how certain limitations might stem from the generalized structure of the model, or from structural assumptions. The reviewer suggestions and resulting changes provided a clearer discussion of the methods and their limitations. The resulting paper provides a careful and well documented contribution for scholars working with similarity-based network approaches in archaeology.

    References

    Paula Gheorghiade, Tom Brughmans, Michele Coscia, Nikolaos Salamanos (forthcoming) A Framework for Identifying Past Social Networks from Material Culture Similarity. Journal of Archaeological Method and Theory.

    Robert J. Bischoff, Cecilia Padilla-Iglesias (2026) Bridging Material Culture Networks and Social Networks in Archaeology. SocArXiv, ver.2 peer-reviewed and recommended by PCI Archaeology https://doi.org/10.31235/osf.io/wjsyg_v2

  4. Peer Community in Archaeology

    The overall reviews for this paper were quite positive, and I think that the content discussed and addressed in this paper will be of interest to the wider archaeological community dealing with model building, and modelling past social processes. Before fully recommending the pre-print, however, I think the authors could benefit from addressing some of the points reviewers brought up during the review process, that could improve clarity on some points. I look forward to reading the final version.

  5. Peer Community in Archaeology

    A valuable study that provides critical footing for users of archaeological network analyses to approach their methods, data, and interpretation more critically, robustly, and empirically.

     

    Title and abstract

    • Does the title clearly reflect the content of the article? [X ] Yes, [ ] No (please explain), [ ] I don’t know
    • Does the abstract present the main findings of the study? [X ] Yes, [ ] No (please explain), [ ] I don’t know

    Introduction

    • Are the research questions/hypotheses/predictions clearly presented? [X ] Yes, [ ] No (please explain), [ ] I don’t know
    • Does the introduction build on relevant research in the field? [X ] Yes, [ ] No (please explain), [ ] I don’t know

    Materials and methods

    • Are the methods and analyses sufficiently detailed to allow replication by other researchers? [ X] Yes, [ ] No (please explain), [ ] I don’t know
    • If applicable (for empirical studies), are sample sizes are clearly justified? [ X] Yes, [ ] No (please explain), [ ] I don’t know
    • Are the methods and statistical analyses appropriate and well described? [X ] Yes, [ ] No (please explain), [ ] I don’t know

    Results

    • In the case of negative results, is there a statistical power analysis (or an adequate Bayesian analysis or equivalence testing)? [ ] Yes, [ ] No (please explain), [ ] I don’t know
    • Are the results described and interpreted correctly? [X ] Yes, [ ] No (please explain), [ ] I don’t know

    Discussion

    • Have the authors appropriately emphasized the strengths and limitations of their study/theory/methods/argument? [X ] Yes, [ ] No (please explain), [ ] I don’t know
    • Are the conclusions adequately supported by the results (without overstating the implications of the findings)? [X ] Yes, [ ] No (please explain), [ ] I don’t know

  7. Peer Community in Archaeology

    This paper explores the - often tacitly held but rarely explicitly addressed or tested – correlation between material networks and social networks. The paper offers an important contribution to the field using a sound methodology based on computational modelling and multiple statistical measures for network comparison and analysis.The results are properly described and the conclusions drawn from them are well-balanced. The documentation of the model and analyses conducted for this paper is sufficiently extensive and adheres to current best practices.

    I only have a handful of smaller comments or remarks pertaining to some elements that could merit a deeper discussion.

    Comments:

    p. 6: “Re-sampling networks has shown that many large networks are robust to missing nodes (Gjesfjeld 2015; Peeples et al. 2016), as long as the samples are random or non-biased (Bischoff et al. 2024).”

    ·       I do not want to push you to cite my own work, but I would just like to point out a recent paper that would be very relevant here discussing the robustness of archaeological networks for the effect of time-averaging: Daems, D., Coco, E., Gillreath-Brown, A., & Kafetzaki, D. (2024). The Effects of Time-Averaging on Archaeological Networks. Journal of Archaeological Method and Theory, 31(2), 473–506. https://doi.org/10.1007/s10816-023-09608-7

    p. 13: how is the QAP test calculated? For graph correlation and ERGM the associated R packages are mentioned, but not for QAP.

    p. 15: Table 3: “Combined” networks listed in table but not explained or discussed in the text.

    p.19-20: “Note that the triangle model was attempted with only the edge and band parameter but in most cases the model failed to converge, which is a recognized issue in the ergm package” + “Unfortunately, the ergm function in R has a tendency to fail when trying to replicate certain network structures and some ERGMs did not return results.”

    ·       Recognized issues or not, you should discuss both observations in more depth. How did it impact the analysis? What are the repercussions for the results? Are there work-arounds that you tried but that did not yield the desired results or are there workarounds you could not try and for what reason?

     p.21: “This is an example of a limitation of a generalized ABM where the results cannot adequately represent empirical data.”

    ·       I suspect it is more a consequence of the way the model is set up, rather than of it being a generalized model that has difficulties representing empirical data. Thoughts?

    Title and abstract

    Does the title clearly reflect the content of the article? Yes
    Does the abstract present the main findings of the study? Yes


    Introduction

    Are the research questions/hypotheses/predictions clearly presented? Yes
    Does the introduction build on relevant research in the field? Yes


    Materials and methods

    Are the methods and analyses sufficiently detailed to allow replication by other researchers? Yes
    If applicable (for empirical studies), are sample sizes clearly justified? Not applicable
    Are the methods and statistical analyses appropriate and well described? Yes


    Results

    In the case of negative results, is there a statistical power analysis (or an adequate Bayesian analysis or equivalence testing)? Not relevant
    Are the results described and interpreted correctly? Mostly


    Discussion

    Have the authors appropriately emphasized the strengths and limitations of their study/theory/methods/argument? Yes
    Are the conclusions adequately supported by the results (without overstating the implications of the findings)? Yes

     

  8. Peer Community in Archaeology

    The article addresses a fundamental issue in the field of archaeology, and one that is of particular interest to those of us engaged in building models to study past societies through material culture: the relationship between social interactions and material culture. To explore this, the authors employ a methodology with which they are clearly well acquainted, as demonstrated by their previous high-impact publications. This methodology is agent-based modelling, used here to simulate in abstract form two types of networks: social and material networks.

    They use the ArchMatNet model, which reproduces hunter-gatherer communities within a controlled environment. The study then compares the generated networks of social interaction with networks derived from the similarity of artifact assemblages. This similarity can be stylistic or functional (referred to by the authors as “pots” and “points”). Based on these data, the authors apply different network analysis tools to assess the extent to which material patterns reflect social ones. The idea is brilliant, and the research question has been addressed in an excellent way. By adopting an experimental perspective, the authors successfully isolate key factors that allow material culture to serve as a proxy for studying social relationships.

    The authors’ efforts to ensure the reproducibility of their work are also highly commendable. The data are openly available and can be accessed and evaluated transparently.

    From a formal standpoint, the structure of the text is correct. However, parts of the introduction that explain ABM and network analysis in archaeology, as well as the section on ArchMatNet, could be more appropriately placed within the methodological section. It could also be useful to add a discussion section that would include part of the current section 0.5, “Conclusion.”
    The text is also characterised by a rather high technical density, which might be somewhat demanding for readers less familiar with modelling or network analysis tools. For instance, in line 263, it might be advisable to add a brief explanation of the Jaccard index. Likewise, when discussing the three methods of network comparison and statistical analysis in section 0.3 (Methodology), this part could benefit from a clearer and more didactic explanation of each method.

    In any case, it is understandable that in a study of this kind, providing detailed explanations of all the statistical measures and analytical tools employed could easily exceed the word limit set by most academic journals. Nevertheless, in Humanities it is always necessary to find a balance that ensures the work remains comprehensible to the widest possible audience.

    These suggestions do not detract from the overall value of this solid, innovative, and methodologically well-constructed work. 


    Title and abstract
    • Does the title clearly reflect the content of the article? Yes
    • Does the abstract present the main findings of the study? Yes
    Introduction
    • Are the research questions/hypotheses/predictions clearly presented? Yes
    • Does the introduction build on relevant research in the field? Yes
    Materials and methods
    • Are the methods and analyses sufficiently detailed to allow replication by other researchers? Yes
    • Are the methods and statistical analyses appropriate and well described? Yes
    Results
    • Are the results described and interpreted correctly? Yes
    Discussion
    • Have the authors appropriately emphasized the strengths and limitations of their study/theory/methods/argument? Yes
    • Are the conclusions adequately supported by the results (without overstating the implications of the findings)? Yes

  9. Version published to 10.31235/osf.io/wjsyg_v3 on OSF Preprints
  10. Version published to 10.31235/osf.io/wjsyg_v2 on OSF Preprints
  11. Version published to 10.31235/osf.io/wjsyg_v1 on OSF Preprints