Diane K. Jakacki
Christine Loflin's teaching and learning site | Do some good, have some fun
Last week, I had the very real pleasure of attending a Word Vectors for the Thoughtful Humanist workshop. This workshop was hosted by Northeastern’s Women Writers Project (WWP) and was sponsored by a grant from the NEH’s Office of Digital Humanities . The principal instructors throughout the week were Julia Flanders and Sarah Connell , respectively the WWP Director and Assistant Director.
I have a lot that I could say about the workshop, and I hope to collect some thoughts in some short blog posts over the coming days. The idea is that if I try to write some short thoughts rather than say everything , I might end up saying something . But I’ve got to start somewhere, and where I want to start is trying to explain word vectors to myself. I expect that this exercise will prove useful to retain some of what I learned last week, as well as prepare me to share this methodology with my students,
Put very simply, word vectors are a means to represent linguistic data in multi-dimensional space and calculate their similarity. The algorithm—normally word2vec or GloVe —looks at a word and its neighbors within a window that the researcher sets (e.g. 5 words to either side of the key word). Each token (individual word) is converted into a type (which is to say that “marriage” only appears once in the model) and then placed in vector space. These placements are essentially random as the window moves acros
Diane K. Jakacki
Christine Loflin's teaching and learning site | Do some good, have some fun