Within the context of the ID-N project NIKAW, funded by the Special Research Fund (BOF) of KU Leuven, we are inviting applications for a PhD position on the subject of social network analysis based on the mentions of people in ancient texts.

The set of thoughts, ideas, and beliefs that are shared, discussed, and enriched in a society is a complex and dynamic reality, constantly fed by and giving way to historical events. Nowadays, the easy access to social network and telecommunication data, online publications, and, for instance, book sales data, has increased our possibilities of analyzing this flow of information incredibly. In this project, however, we want to investigate how we can map the circulation of ideas and identify pivotal individuals in past societies, namely the Graeco-Roman world, whose fragmented history, encompassing many centuries, can only be studied through partial remainders. To this end, the NIKAW project aims to exploit textual information from the ancient world to reconstruct the transmission of knowledge across multilingual, geographically and chronologically extended communities.

The PhD candidate will focus on the study of the relations emerging from the mentions of names in Greek and Latin texts. Part of the tasks will be carried out in collaboration with another PhD student and one Postdoc. Using a large set of automatically retrieved passages, gathered by the other PhD scholar, the candidate will reconstruct and exploit the network of intellectual relations over a large span of time. A particular test-case on the first stages of the advent of Christianity is foreseen. Research will be carried out along two tracks:

Firstly, the candidate will develop a graph database model to properly represent the mentions of people in ancient texts. To this end, the candidate will work closely with the PhD scholar working on the extraction and disambiguation of names in ancient texts. 

Secondly, the candidate will use the graph database to reconstruct and analyze the network of mentions in ancient texts, applying tools of Social Network Analysis. In collaboration with the Postdoctoral scholar, the candidate will also investigate the application of more advanced techniques such as learning relevant structural features with the use of network embeddings. In particular, the PhD student will analyze the changes in the network in the first four centuries of the Common Era, observing how the integration of Christian authors impacts relevant network features.

The candidate is expected to start in November or a soon as possible afterwards and, based on their profile, will be supervised by one or more project (co)PIs.