Pilot study for the COST Action "Reassembling the Republic of Letters": language-driven network analysis of letters from the Hartlib's Papers

TL;DR

This pilot study applies NLP and network analysis to 17th-century letters from Hartlib Papers to identify key entities and relationships, demonstrating a methodological approach for historical letter network analysis.

Contribution

It introduces an NLP pipeline for converting historical letters into network representations to analyze narrative centrality and relationships.

Findings

Identified central entities in 17th-century letters

Developed a pipeline for processing historical texts into networks

Showed potential for network analysis in historical studies

Abstract

The present report summarizes an exploratory study which we carried out in the context of the COST Action IS1310 "Reassembling the Republic of Letters, 1500-1800", and which is relevant to the activities of Working Group 3 "Texts and Topics" and Working Group 2 "People and Networks". In this study we investigated the use of Natural Language Processing (NLP) and Network Text Analysis on a small sample of seventeenth-century letters selected from Hartlib Papers, whose records are in one of the catalogues of Early Modern Letters Online (EMLO) and whose online edition is available on the website of the Humanities Research Institute at the University of Sheffield (http://www.hrionline.ac.uk/hartlib/). We outline the NLP pipeline used to automatically process the texts into a network representation, in order to identify the texts' "narrative centrality", i.e. the most central entities in the texts, and the relations between them.