Social networks are analysed to identify connections between archaeological phenomena, such as pottery assemblages, communication networks, and sites. This can be done by linking these phenomena...Show moreSocial networks are analysed to identify connections between archaeological phenomena, such as pottery assemblages, communication networks, and sites. This can be done by linking these phenomena using statistical methods or abstract network models. However, the use of abstract, computer-generated networks to study empirical datasets has been underused in archaeology. Therefore, employing computational models from other academic disciplines can benefit from this lack of abstract network analysis. This study analyses how various computer-generated networks influence the rate of adoption of the Bell Beaker pottery in the Lower Rhine Region. The Bell Beaker pottery is a Late Neolithic and Early Bronze Age material culture that had been widespread across Western and Central Europe. For more than a century, there has been much debate on how the Bell Beaker phenomenon became prevalent in the archaeological record. The spread of the Bell Beaker pottery can be analysed in the context of the Lower Rhine Region by using the sociological concept of diffusion of innovations. In this thesis, the diffusion of innovations is applied to an agent-based model in which the spread of the Bell Beaker phenomenon in the Lower Rhine Region is simulated. In this model, various computer-generated networks were tested to analyse which network type fits the Bell Beaker data the best. This data is comprised of pottery frequencies from settlement sites which were chronologically organised to show how the Bell Beaker pottery was distributed over time. The results from the simulation were compared to the communication network of the Lower Rhine Region devised by Kleijne (2019). The results of this comparison show that the diffusion of the Bell Beaker phenomenon was initially fast but stagnated later in time. The diffusion was transmitted over a network structure in which a few nodes have a central position in connecting the entire network (scale-free network). The results indicate that using abstract, computer-generated networks is a suitable approach to assessing archaeological networks. Additionally, the application of theoretical and computational models from other academic disciplines can contribute to archaeological theory building. Further research is needed to test other types of network structures that were not applicable to the model used in this thesis.Show less