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Full-Text Articles in Computational Linguistics
Topics For He But Not For She: Quantifying And Classifying Gender Bias In The Media, Tyler J. Lanni
Topics For He But Not For She: Quantifying And Classifying Gender Bias In The Media, Tyler J. Lanni
Dissertations, Theses, and Capstone Projects
In this study, we used computational techniques to analyze the language used in news articles to describe female and male politicians. Our corpus included 370 subtexts for male candidates and 374 subtexts for female candidates, gathered through the New York Times API. We conducted two experiments: an LDA topic analysis to explore the data, and a logistic regression to classify the subtexts as either male or female. Our analysis revealed some noteworthy findings that suggest the possibility of developing a gender bias classifier in the future. However, to create a more robust understanding of bias, additional research and data are …
A Sentiment Analysis Of Language & Gender Using Word Embedding Models, Ellyn Rolleston Keith
A Sentiment Analysis Of Language & Gender Using Word Embedding Models, Ellyn Rolleston Keith
Dissertations, Theses, and Capstone Projects
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 …