Recent Posts

Do wikipedia editors specialize?

Do wikipedia editors specialize?

One of the students in our lab, Nathan Drezner, has a new collaboration out entitled, “Everyday Specialization: The coherence of editorial communities on Wikipedia.” In this paper, Drezner studies edit histories of over 30,000 Wiki pages across four different cultural domains (science, sports, culture, and 

Can We Be Wrong?

Can We Be Wrong?

I have a new book out. It’s called “Can We Be Wrong? The Problem of Textual Evidence in a Time of Data.” The goal of the book is to change the terms of debate surrounding the place of computational literary analysis within the field literary 

Measuring Unreading

Measuring Unreading

In a new piece out in the Goethe Yearbook, I and my co-author, student James Manalad, use text re-use algorithms to better understand citational practices within scholarly publications. In particular we look at how Goethe’s collected works are directly quoted in 68 volumes of the 

How do disciplines change?

How do disciplines change?

Over the past few years I’ve become interested in better understanding how my own discipline works. As someone whose work has changed considerably over the past decade, it’s probably a predictable response. In one sense, it is about asking, How do I fit in? On 

The scientization of literary studies

The scientization of literary studies

In a new work out, I have teamed-up with my collaborator Stephania DeGaetano-Ortlieb to try to model what we call “the scientization of literary study.” The study of literature has historically been seen as a scholarly practice that is distinct from the natural sciences. Literary 

Let’s talk about debiasing books – Webinar

Let’s talk about debiasing books – Webinar

As part of BookNet Canada‘s on-going webinar series, I recently held a webinar on using data analytics to “debias” books. A lot of discussion has begun in publishing with respect to increasing the diversity of publishers’ lists. The issue is often seen as one that 

Are you genre fluid? A new collaboration on Spotify by Cheng Lin and Benjamin LeBrun

Are you genre fluid? A new collaboration on Spotify by Cheng Lin and Benjamin LeBrun

A new student collaboration is out. It’s called “Streaming Bias: studying music curation on Spotify” and represents the lab’s first attempt at studying online music content. Lin and LeBrun did an amazing job in conceptualizing the project and working tirelessly from data collection to analysis 

Covid and Cultural Analytics

Covid and Cultural Analytics

If you’re like me, you’re probably feeling overwhelmed right now. Continuing to do academic research in this climate is very hard, to say the least. But if you’re like me, you’ve probably also asked yourself more than a few times, is there something I can