Using Data Analytics and Network Visualisation to Inform Future Collecting and Research Practice in Hybrid Literary Archives (Coleridge Fellowship)
Using Data Analytics and Network Visualisation to Inform Future Collecting and Research Practice in Hybrid Literary Archives (Coleridge Fellowship)
Using Data Analytics and Network Visualisation to Inform Future Collecting and Research Practice in Hybrid Literary Archives (Coleridge Fellowship)
This collection contains the outputs for a project funded by a Coleridge Research Fellowship at the British Library.
This pilot project uses data analytics in Python and network analysis in Gephi to interrogate the ways in which digital and analogue correspondence files (letters and e-mails) function within the Archive of Harold Pinter; reflecting upon what these patterns might mean for archivists, curators and researchers working with hybrid correspondence collections.
The work was completed part-time over a six month period (September 2022-March 2023) by the Principal Investigator, Callum McKean (Lead Curator of Born Digital Archives and Manuscripts at the British Library) and the Project Assistant, Cameron Randall (Manuscripts Cataloguer).
- Some of the metrics are blocked by yourconsent settings
Item type:Software, Hybrid Correspondence Network Processing Script(2023-08-11)Mckean, CallumThe Python code was developed to to interrogate the ways in which digital and analogue correspondence files (letters and e-mails) function within the Archive of Harold Pinter; reflecting upon what these patterns might mean for archivists, curators and researchers working with hybrid correspondence collections. This code is collection agnostic and its outputs are compliant with General Data Protection Regulation in the UK, meaning that interested parties at any collecting repository working with born digital or hybrid archives will be able to re-use the code for their own purposes and that the outputs can be shared within the sector and amongst the wider research community.2 4