This paper demonstrates the analytical potential of graph theory applied to mortuary archaeological data. We focus primarily on the efficient production of dissimilarity matrices, their transformation, and visualization in Social Network Analysis software Pajek. The case study of the Early Bronze Age cemetery Rebešovice (Czech Republic) is used to explore the potential of these analytical tools to explain the contrast between the center and the periphery of the cemetery, which was identified in previous studies. Two hypotheses are proposed to explain this contrast: chronological and social. The first hypothesis explains the difference between the centre and the periphery as a function of time, while the latter as a function of social standing.

The dataset includes archaeological and biological data from 72 graves. We calculate simple matching distance matrix as a measure of dissimilarity among the graves. We produce various simple matching distance matrices based on chronologically or socially significant variables. Then, we select a cut-off value of dissimilarity and transform the simple matching distance matrices into adjacency matrices. Finally, we model and visualize the results in Pajek using the space defined  by real geographic coordinates. The results of this methodological exploration are discussed in context of other analytical approaches used in mortuary studies to investigate intra-cemetery mortuary variability.