Integrating ancient DNA–derived networks of biological kinship with demographic and cultural variables presents a significant methodological challenge.

We first introduced the method in Wang et al. 2025 via an analysis of Avar cemteries in Austria. However, we saw a generalised need for the method, and wrote a paper describing the method that has now been accepted for publication.

In our methods paper, we demonstrate that Exponential Random Graph Models (ERGMs) provide a statistically-rigorous framework for detecting and quantifying the factors that structure such networks. We then apply ERGMs to individuals from four 6th-9th-century Hungarian Avar cemeteries. We confirm a pattern of female-biased mobility consistent with women relocating to reside with their partners, and show that biologically-related individuals are more likely to share burial customs. Finally, we find that individuals buried with elite horse-riding equipment are more likely to be related, suggesting social stratification. Together, we establish a robust methodological approach for investigating ancient biological-kinship networks that offer new insights into the cultural practices and everyday lives of past populations. 

Work done with my colleagues: