Quantitative network analysis offers a powerful way to explore correspondence networks to uncover the large-scale spatial and temporal characteristics of power structures, communication patterns, and recording practices. To support this, we will provide humanities scholars with improved tools and infrastructure to allow network analysis on large datasets.

This will be accomplished, first, by a locally installed, simple web-application that employs algorithms from the NetworkX library to allow users to easily perform a subset of network analysis techniques. The tool will serve as the primary means for introducing network analysis in the project’s training schools. While the interface described above is a useful starting point, it cannot address the wide range of advanced research avenues that quantitative approaches enable. For this reason, the project will also develop a set of bespoke Python scripts to explore more complex tasks, such as the analysis of overlapping and temporal networks with arbitrary edge data.

To make it easier for researchers to access the curated meta-archive, Early Modern Letters Online (EMLO) will be enhanced to filter and search records based on basic quantitative network measures such as degree, strength and centrality. This will be coupled with new means for users to export on-demand entire catalogues or the results of custom search queries to simplify the reuse of this data in external tools. Additionally, developers will gain the ability to query and export EMLO data via a new REST API.

All software components and infrastructure developed during the project will be shared under open-source licenses, consolidated into standalone, Docker containers, and their build scripts shared on our GitHub repository.