Word Embeddings for Social Scientists and Humanists
The goal of this notebook is to demystify some of the technical aspects of language models and to invite learners to start thinking about how these important tools function in society. In particular, this lesson is designed to explore features of word embeddings produced through the word2vec model. The questions we ask in this lesson are guided by Ben Schmidt’s blog post, Rejecting the Gender Binary.
Laura K. Nelson
Associate Professor of Sociology
I use computational methods to study social movements, culture, gender, institutions, and the history of feminism. I’m particularly interested in developing transparent and reproducible text analysis methods for sociology using open-source tools.