Social network theory postulates that in diverse social contexts individuals and groups can generate and sustain numerous diversely oriented relationships and networks of relationships. At the same time, narrative networks and character networks, in which socially effective relationships are constructed, play a very important role in literary studies and in the study of historical sources, including those of late antiquity and early Christianity, such as prosopographies or exilic accounts. Intentionally and unintentionally created structures in such textual sources, invisible in direct source study, can be determined by a combination of both approaches. The mathematical analysis necessary for this goes far beyond simple methods of Distant Reading, but allows deep insights into the self-representation of ancient authors, into implicitly existing social networks, and furthermore enables an analysis of dependencies and power structures based on different ways of naming persons, their namelessness, their described gender identity, and of course their role and position in social networks.

In the project, on the one hand, an online-accessible and, on the other hand, a mathematically adaptable tool is to be built that extracts persons with the help of AI-based methods of NLP such as Named Entity Recognition and, on the other hand, calculates social networks of these persons with mathematical classical network analysis.