23-26 April 2014
Vienna University, Universitätsring 1, 1010 Vienna, Austria
Between 1783 and 1840, the number of newspapers published in Scotland grew tenfold and spread far beyond the key port towns of Glasgow, Edinburgh, and Aberdeen into market towns and centres throughout the region. Although these provincial newspapers remained weekly or bi-weekly publications throughout the period, they still required a significant amount of international reportage to fill their four to eight pages. This material was shamelessly, and often haphazardly, gleaned from international periodicals in the form of scissors-and-paste reprints. Through these half-hearted shortcuts, we can develop a significant understanding of newspaper networks before the rise of international telegraphy and the slow decline of the scissors-and-paste system.
Utilising highly detailed transcriptions of newspaper content from Scotland, England and the wider Anglophone world, this paper will trace key dissemination pathways of news content from its origin in various British colonies, through its many reprints, abridgments, summaries and commentaries, to the pages of Scottish periodical press. By mapping the shape and directionality of these network connections, a greater understanding of news dissemination and editorial links can be achieved. These networks can then form the statistical basis of further qualitative studies into the spread of ideas or interpersonal connections.
The paper will demonstrate how, through a combination of traditional close reading, ‘big data’ edition tracking, and social network analysis, Georgian news networks, including periodicals with extremely short runs and no contextual records, can be significantly mapped and the quantitative influence of key hubs can be preliminarily determined. It will explore the relative value of manual and computer-assisted transcriptions at different stages of the project, the feasibility of training historians in high-level programming languages such as Python, the nature of the resulting network data and its interoperability with mathematical and sociology research, and the possibilities for wider dissemination and collective re-use of transcription data.
**Image courtesy of Lukas Stifter