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Blogging as a digital means of research communication seems so simple: with free, easy-to-use platforms we’re all just a few clicks away from setting one up. But having set a blog up, the difficult work begins. Who are you talking to? What are you trying to achieve? How will you generate your content? How will the people you want to talk to find it? How are you going to keep it going alongside your research and teaching commitments? Will it make any difference to anything? And will you ever be able to transform any of this work into a scholarly publication that ‘counts’?

This session will be an interactive conversation between Julie Blake, Cambridge Digital Humanities Methods Fellow and Connie Ruzich, University Professor of English at Robert Morris University, Pittsburgh, USA. Connie’s Behind Their Lines blog started in 2014 during a Fulbright Scholarship at Exeter University to research First World War poetry in the context of the Centenary Commemorations. She became interested in the lost and neglected poetry of the First World War and began blogging about her ‘finds’. Five years later, she has had almost 400,000 visits to her blog, she maintains a lively dialogue with public and academic audiences including via Twitter and she is in the final stages of completing a monograph about this material with Bloomsbury Academic.

We’ll discuss the highs and lows of Connie’s research blogging experience, the surprises, the pitfalls and the lessons learned by hard won experience. We’ll try to answer all the questions listed above, and participants will be invited to join in with their own questions.

Speaker: Mark Algee-Hewitt, Associate Professor of English and Director of the Stanford Literary Lab.

About this Methods workshop

At the heart of many of the current computational models of language usage, from generative A.I. to recommendation engines, are large language models that relate hundreds of thousands, or millions, of words to each other based on shared contexts. Mysterious products of complex modelling algorithms, these objects raise a number of practical (and ethical) questions for Humanities scholars: How are these language models created? What kinds of relationships does their math encode? How do biases in the corpus affect the model? And how can we effectively use them to answer humanities-based questions?

In this workshop, we will explore these questions using a medium-sized language embedding model trained on a corpus of novels. Using approachable code in the R software environment, participants will learn how to manipulate a model, assess similarities and difference within it, visualise relationships between words and even train their own embeddings.

The aim of this course is to support students, researchers, and professionals interested in exploring the changing nature of the English vocabulary in historical texts at scale, and to reflect critically on the limitations of these computational analyses. We will focus on computational methods for representing word meaning and word meaning change from large-scale historical text corpora. The corpus used will consist of Darwin’s letters from the (Darwin Project https://www.darwinproject.ac.uk/) at Cambridge University Library. All code will be in online Python notebooks.

If you are interested in attending this course, please fill in the application form