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Social Network Analysis of Ancient Japanese Obsidian Artifacts Reflecting Sampling Bias Reductionuse asterix (*) to get italics
Fumihiro Sakahira, Hiro’omi TsumuraPlease use the format "First name initials family name" as in "Marie S. Curie, Niels H. D. Bohr, Albert Einstein, John R. R. Tolkien, Donna T. Strickland"
<p>This study aims to investigate the dynamics of obsidian trade networks during the Jomon period (approximately 15,000 to 2,400 years ago), the hunting and gathering era in Japan. To improve regional representation and reduce the distortions caused by small sample sizes, we performed clustering based on a large-scale dataset and conducted social network analysis. The research results revealed that the trade networks during the Jomon period were not constant; they expanded throughout the southern Kanto region during the Middle Jomon period (5,500–4,500 years cal BP) and ceased to function during the Late Jomon period (4,500–3,200 years cal BP). Furthermore, to enhance the readability and interpretability of the dataset, we implemented clustering using the density-based spatial clustering of applications with noise (DBSCAN) method. The results showed that in every time division of the Jomon period, the mean intra-cluster cosine similarity of each cluster was higher than the similarity between sites outside the clusters, confirming the reasonableness of an analysis considering regional representation. In addition, to verify the robustness of the network in the social network analysis after clustering, we also performed a bootstrap simulation analysis. The results showed high network robustness and demonstrated that the sampling after clustering had minimal impact on this study’s findings.</p> should fill this box only if you chose 'All or part of the results presented in this preprint are based on data'. URL must start with http:// or https:// should fill this box only if you chose 'Scripts were used to obtain or analyze the results'. URL must start with http:// or https://
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social network analysis, obsidian artifact, DBSCAN, clustering, ancient Japan, Jomon period
NonePlease indicate the methods that may require specialised expertise during the peer review process (use a comma to separate various required expertises).
Asia, Computational archaeology
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Naoko Matsumoto [,]e.g. John Doe []
2023-05-28 05:51:12
James Allison
Thegn Ladefoged, Matthew Peeples