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

The applications of Social Network Analysis [Scott, 2013] to literary and historical texts have attracted a growing interest in the scholarly community as powerful tools to investigate social structures. At the same time, the increased access to large amounts of digitized historical texts and the availability of corpus tools and computational methods for analysing those data in automatic ways offer new answers to humanistic research questions. Over the past decades, an increasing number of academic projects have focused on the role played by corpora in historical investigations, and several studies have shown that historical corpora contribute effectively to the progress of historical research (cf. e.g. Knooihuizena and Dediub 2012, Piotrowski 2012). 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 [Popping and Roberts, 1997, Diesner and Carley, 2004] 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. We will outline the NLP pipeline used to automatically process the texts into a network representation following the approach by Sudhahar et al. [2015], van de Camp and van den Bosch [2011], in order to identify the texts’ “narrative centrality”, i.e. the most central entities in the texts, and the relations between them. Network Text Analysis is typically applied to a large quantity of text, hence our goal is not to provide a complete analysis of the letters under investigation. We will instead aim to make an initial assessment of the validity of this approach, to suggest how it can scale up to a much larger set of letters, and to define which infrastructure would be needed to extend this process to a potentially multilingual historical corpus of epistolary texts.