Date of Degree
Anthropological Linguistics and Sociolinguistics | Computational Linguistics
sociolinguistics, sentiment analysis, word embedding models, topic modeling
Since Robin Lakoff started the conversation around language and gender with her 1975 essay “Language and Woman’s Place,” extensive work has been done on analyzing sociolinguistics associated with gender. While much work has been done on the differences between how men and women use language, there is less research to be found on language about women as opposed to language about men. In this work, I build a word embedding model from a corpus of Wikipedia film summaries and use this model to create lists of words associated with men and words associated with women. I then use sentiment analysis tools to assess the emotional valence of these words and sentences containing them. I find that when comparing words and sentences associated with men and women, language about women tends to be more consistently more positively valenced, while words associated with men cover a wider breadth of valences, skewing slightly negative.
Keith, Ellyn Rolleston, "A Sentiment Analysis of Language & Gender Using Word Embedding Models" (2017). CUNY Academic Works.