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  • Porter et al, IJHAC 2018

    Rights statement: This is an Accepted Manuscript of an article that will be published by Edinburgh University Press in the International Journal of Humanities and Arts Computing (2018, vol 12:2). The Version of Record will be available online at: https://www.euppublishing.com/loi/IJHAC. This Accepted Manuscript is copyright of the authors and is available under a Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License. For example: 'This is an Accepted Manuscript of an article published by Edinburgh University Press in Word Structure. The Version of Record is available online at: http://www.euppublishing.com/doi/abs/10.3366/word.2017.0099.'

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Health and disease in nineteenth-century newspaper: A textual and geographical analysis of a large newspaper corpus

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<mark>Journal publication date</mark>27/03/2018
<mark>Journal</mark>International Journal of Humanities and Arts Computing
Issue number2
Volume12
<mark>State</mark>Accepted/In press
<mark>Original language</mark>English

Abstract

The abundance of information contained in nineteenth-century texts means the traditional ‘close reading’ of Victorian culture has limitations (Nicholson, 2012). Due to its sheer volume, historic newspaper text is one genre that has suffered from such methodological limitations, research questions and outputs often constrained by traditional approaches. With the increasing burgeoning availability of newspapers in digital format, there is a pressing need to look at how we might effectively and efficiently use these digital resources to help answer research questions and add to key historical and geographical debates. Focusing on the analysis of a large digital corpus, this paper has two key foci: (I) to extend on a new tried and tested methodology for the assessment of digital texts using a combination for corpus linguistics and geospatial technologies; and ; (II) apply said methodology to a case study assessing the presentation of health and disease in a nineteenth-century newspaper. The paper illustrates, for the first time, that by linking existing techniques with new and innovative approaches it is possible to temporally and spatially analyse and map themes of interest in large digital texts corpora on a scale not possible through more traditional close reading methods.