Affiliation:
1. School of Computer Science and Insight SFI Research Centre for Data Analytics, University College Dublin , Ireland
2. Department of Digital Humanities, University College Cork , Ireland
3. Management School, University of Sheffield , United Kingdom
Abstract
Abstract
The interview has always proved to be a rich source for those hoping to better understand the figures behind a text, as well as any social contexts and writing practices which might have informed their aesthetic sentiments. Over the past two decades, research into the literary interview has made significant strides, both in terms of how this literary genre is conceptualized and how its emergence and development has been historically traced, the form remains somewhat neglected by literary and cultural theorists and scholars. There is also a remarkable absence of distant readings in this domain. With the rise of the digital humanities, particularly digital literary studies, one would expect more scholars to have used computer-assisted techniques to mine literary interviews, which are, in terms of dataset practicalities, somewhat ideal, semi-structured by nature, and typically available online. Such is the question to which this article attends, taking as its dataset seven decades’ worth of literary interviews from The Paris Review, and ‘topic modelling’ these documents to determine the key themes that dominate such a culturally significant set of materials while also exploring the value of topic modelling to socio-literary criticism.
Publisher
Oxford University Press (OUP)
Reference50 articles.
1. The Paris Review Interviews, Volume 1 (Review)’,;Anglade;The Missouri Review,2006
2. ‘Latent Dirichlet Allocation’;Blei;Journal of Machine Learning Research,2003
3. ‘Topic Modelling and Digital Humanities’;Blei;Journal of Digital Humanities,2013