Understanding the romanization spreading on historical interregional networks in Northern Tunisia

Abstract

Spreading processes are important drivers of change in social systems. To understand the mechanisms of spreading it is fundamental to have information about the underlying contact network and the dynamical parameters of the process. However, in many real-wold examples, this information is not known and needs to be inferred from data. State-of-the-art spreading inference methods have mostly been applied to modern social systems, as they rely on availability of very detailed data. In this paper we study the inference challenges for historical spreading processes, for which only very fragmented information is available. To cope with this problem, we extend existing network models by formulating a model on a mesoscale with temporal spreading rate. Furthermore, we formulate the respective parameter inference problem for the extended model. We apply our approach to the romanization process of Northern Tunisia, a scarce dataset, and study properties of the inferred time-evolving interregional networks. As a result, we show that (1) optimal solutions consist of very different network structures and spreading rate functions; and that (2) these diverse solutions produce very similar spreading patterns. Finally, we discuss how inferred dominant interregional connections are related to available archaeological traces. Historical networks resulting from our approach can help understanding complex processes of cultural change in ancient times.

Research-data management planning in the German mathematical community

“…We consider the documentation of a concrete workflow combining archaeology and mathematics as an example. This is based on [11], was created by Margarita Kostre independently afterwards, and described in personal communication as 'very helpful for the reflection of the own work. ' The author commented that she will use workflow documentation in the future again, as she believes it facilitates interdisciplinary communication, e.g., about the status of a project, its goal, and data transfer, it provides better clarity in larger collaborations and allows colleagues to enter a project more easily.…”

“…Acknowledgements. The authors are grateful to Margarita Kostre for retrospectively compiling an RDMP for her project [11] and to Tim Hasler for background and discussion regarding the MATH+ research-data management organizer.…”