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A performance test of archaeological similarity-based network inference using New Guinean ethnographic data
Journal of Anthropological Archaeology ( IF 2.312 ) Pub Date : 2023-10-17 , DOI: 10.1016/j.jaa.2023.101550
Mark Golitko

Network analysis has become increasingly common within archaeological practice, yet little consensus exists as to what networks based on material culture actually reveal about ancient social life. One common approach to archaeological network inference relies on constructing similarity networks based on shared material types or stylistic categories between archaeological sites or contexts. Many studies implicitly or explicitly assume that the topology of similarity networks is a useful proxy for underlying patterns in ancient social networks, yet this basic assumption has not been rigorously evaluated. Here, I present a preliminary test of how well network measures inferred from material culture—in this case, bone daggers made on the island of New Guinea between 1845 and 2002—predict network measures derived from ethnographic accounts of social engagement between 1720 New Guinea communities. In this case study network distance partially predicts material similarity, and neighborhood/cluster identification algorithms partially identify similar patterning in underlying patterns of inter-community engagement. However, most commonly applied network measures of centrality are not strongly predicted by material cultural similarity. Similarity based network analysis is a powerful means of visualizing and exploring data, and can help in formulating archaeological hypotheses, but may be problematic as a direct inference procedure.



中文翻译:

使用新几内亚民族志数据进行基于考古相似性的网络推理的性能测试

网络分析在考古实践中变得越来越普遍,但对于基于物质文化的网络实际上揭示了古代社会生活的内容却鲜有共识。考古网络推理的一种常见方法依赖于根据考古遗址或环境之间共享的材料类型或风格类别构建相似性网络。许多研究隐含或明确地假设相似网络的拓扑是古代社交网络中潜在模式的有用代理,但这一基本假设尚未经过严格评估。在这里,我对从物质文化推断出的网络测量值(在本例中是 1845 年至 2002 年间在新几内亚岛制造的骨匕首)进行了初步测试,以预测从 1720 个新几内亚社区之间的社会参与的民族志记录中得出的网络测量值。 。在本案例研究中,网络距离部分预测材料相似性,邻域/集群识别算法部分识别社区间参与的基本模式中的相似模式。然而,最常用的网络中心性度量并不能通过物质文化相似性来强烈预测。基于相似性的网络分析是可视化和探索数据的强大手段,可以帮助制定考古假设,但作为直接推理过程可能存在问题。

更新日期:2023-10-17
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