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This is the datatable for my PhD within the NIKAW project. This thesis is part of the interdisciplinary NIKAW-project (Networks of Ideas and Knowledge in the Ancient World), which aims to use state of the art digital methods such as Natural Language Processing (NLP) and Social Network Analysis (SNA) to analyse the circulation of knowledge in Ancient Greek and Latin literary texts. The goal is to capture how historical and cultural changes impacted the network of citations in these texts with deep, long-lasting shifts. The first part of my contribution will focus specifically on the creation of a graph database containing mentions in these texts with as goal identifying and developing strategies for information modelling for mentions. I will populate a graph database with all mentions retrieved automatically linked to historical people. In the second part, I will analyse the citation network’s evolution with a focus on the question of how we can model the circulation of knowledge as a flow reacting to historical events. Using SNA methods, I will attempt to get a picture of the evolution of the citation network and to detect actors with similar roles in the transmission of knowledge. To provide a concrete test case, I will focus on the advent of Christianity in the period from the first to the fourth century CE. In order to see how the citation network changes as a result of cultural shock, I will focus on changes in the network after the publication of the systematizing work the Diuinae Institutiones by Lactantius (an example of endogenous shock) and after the 313 Edict of Milan (an exogenous shock).
Digital Humanities, Greek literature, Latin literature, Ancient History, Social Network Analysis
Digital Humanities, Greek literature, Latin literature, Ancient History, Social Network Analysis
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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