Congratulations to this year’s students!

We have had an excellent year at .txtLAB. I want to send out a special thanks to all of the students who have been contributing to the lab. You’ve made it a great place to work. Here is a list of projects that we’ve been working on this year:

• studying the ambiguity surrounding social interactions in novels
• understanding the semantic differences between prizewinning and bestselling fiction
• developing machine learning techniques to detect practices of scientific illustration in historical documents, beginning with footnotes
• measuring the concentration of elite institutions in high-prestige publications in the humanities
• tracking explicit mentions of time in novels
• creating techniques for detecting narrative frames and plotlines
• understanding the predictability of fictional writing over the past two centuries
• studying gender bias in book reviews
• exploring the quality and quantity of speaking parts in movies by race and gender
• observing the spatial settings of films and TV shows to understand how these media differentiate themselves along a spatial-imaginary
• measuring distributions of character gender across 1,200 contemporary works of fiction from six different genres