Deborah Priß , Christina Prell , Dan Lawrence , Laura Turnbull , John Wainwright
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引用次数: 0
Abstract
Analysing and understanding connectivity of human social networks of (ancient) societies offers new perspectives on their functioning. However, social network approaches in archaeology rarely utilise formal statistical models to test established theories or develop new hypotheses. In this paper, we present the implementation of MCMC-MLE Temporal Exponential Random Graph Models (MTERGMs) to investigate the hollow way network between settlements of the Bronze and Iron Age Khabur Valley, Mesopotamia. Using MTERGMs, we evaluate eight hypotheses to assess which network patterns explain the formation of the hollow ways. Our results show that in the cross-sectional networks, preferential attachment, transitivity, distance and site size are important factors for tie formation while the longitudinal analysis reveals tie persistence over time with distance and transitivity being significant for tie formation. We reflect on these findings as well as the limitations of our dataset and conclude that MTERGMs are useful tools to formally evaluate archaeological theories pertaining to network structures and processes, if the available data are sufficiently complete.
期刊介绍:
The Journal of Archaeological Science is aimed at archaeologists and scientists with particular interests in advancing the development and application of scientific techniques and methodologies to all areas of archaeology. This established monthly journal publishes focus articles, original research papers and major review articles, of wide archaeological significance. The journal provides an international forum for archaeologists and scientists from widely different scientific backgrounds who share a common interest in developing and applying scientific methods to inform major debates through improving the quality and reliability of scientific information derived from archaeological research.