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The use of computational approaches in history is not new (Boonstra et al 2004). However, until fairly recently, their use has been restricted to a relatively small number of fields such as economic history and historical demography. These are fields that make extensive use of quantitative sources, typically in tabular form, that have long been wellsuited to analysis using a computer. Despite the potential benefits of quantitative sources, the overwhelming majority of historians use textual sources and thus, computational approaches have traditionally had little penetration into mainstream history. Over the past decade or so this has changed rapidly. The mass digitisation and dissemination of historical source material such as Early English Books Online (EEBO), Eighteenth Century Collections Online (ECCO), the British Library Newspaper Collections, The Times Digital Archive, Project Gutenberg, and many others have meant that large amounts of historical texts are now available in digital form (Hitchcock 2013). Thus, historians now have access to an unprecedented volume of digitised source material. However, the computational techniques used to analyse such materials them remain rooted in traditional close reading with the digital simply providing ease of access and the use of keyword searching. There is thus a requirement to adopt and adapt the digital approaches available from other fields, and develop new techniques where appropriate, such that scale of the resources available to us can be exploited in a way that is impossible for close reading alone. This challenge is not unique to history; it has occurred across humanities disciples, providing a major impetus to the field of digital humanities (Kirschenbaum 2010; Schreibman et al. 2014; Terras 2016) where a major theme is the use of digital approaches to the analysis of texts in disciplines including English Literature (Moretti 2013; Jockers 2013) and History (Atkinson & Gregory, 2017; Pumfrey et al. 2012).