The UCL Centre for Digital Humanities contributes to and holds a variety of events.

Recurring events include the UCLDH Seminar and the Susan Hockey Lecture series. Our events are primarily advertised right here on this page, which is syndicated in an RSS feed, but also on our DH Blog, on Twitter, and via our mailing list


1st Annual UCL Comparative Literature Tagore Lecture: Novel Analytics from James Joyce to the Bestseller Code

Start: May 10, 2017 6:00:00 PM
End: May 10, 2017 7:00:00 PM

To better understand bestselling fiction, Matthew Jockers and research partner Jodie Archer took the advice of Google researchers who argue that we should "embrace complexity and make use of the best ally we have: the unreasonable effectiveness of data.” Instead of seeking a formula or telling authors how to write a successful novel, Jockers and Archer went to the books, thousands of them, and leveraged computation to ask a simple question: "what are these texts made of?" The bold claim of their research, documented in The Bestseller Code, is that novels that hit the New York Times bestseller list are not random lottery winners but books that share an uncanny number of textual features. In this lecture, Jockers will describe how he went from being a close reader of language in Joyce's Ulysses to mining thousands of novels in search of the linguistic patterns most typical to books that best sell.

Digital Heritage 'Big' Data Hacking & Visualisation

Start: May 22, 2017 9:30:00 AM
End: May 22, 2017 5:00:00 PM

This workshop will discuss expressive uses of ‘big data’ visualisations to engage citizens with the results of research into the human past and its contemporary legacies.

Baseless Data? Developing an ethnographic approach to big data problems

Start: May 24, 2017 5:30:00 PM
End: May 24, 2017 6:30:00 PM

This paper looks at how practices of scientific analysis are being put under strain by the appearance and necessity of working with new kinds of data. Whilst most commentary about big data have focused on the value and ethics of analysing and using transactional consumer data, this paper is concerned with the analytical challenge of another field of ‘big’ data – that of environmental modelling.