My PhD thesis will be a hybrid of Digital Research Methods (DRM) and Social Network Analysis. It utilises DRM and the development of a digital toolkit for the examination of 19c manuscript catalogues to analyse the social connectivity within and between one social group (Quakers in Britain) and others committed to social action in the period 1830 – 1870.
Topics
DRM, graphdata, SQL, python, Quakers
About Kelvin Beer-Jones
(United Kingdom)
The Historical Data Digital Toolkit (HDDT) supports a variety of historical, sociological and anthropological research needs and enables historians to interrogate biographical data found in the catalogues of very large 19c manuscript collections. The toolkit enables tabular and graph data at both high and granular levels to be visualised – from individuals to complex historical communities. It can combine datasets from the catalogues of several archives. The toolkit works with both static and dynamic data (time series) allowing the historian to analyse how and when individual and group relationships and social interests change. Tools deployed are all open source and can be installed on a standard laptop.
The HDDT uses CSV datasheets to generate an SQL relational database. Data from the Royal Anthropological Institute is combined with data from the Quaker Family History Society, and national Quaker archives. Jupyter Notebooks (pandas, Matplotlib) and graph data technology (Gephi) facilitate visualisation of the biographical data and changing social networks amongst 3500 social activists from 1830 to 1870, and in greater detail the 700 or so Quakers amongst them.
