The gender pay gap is one of the serious issues in the labor market today and closing the gap is the major theme in the Equal Pay movement. This gap cannot be simply explained by any common labor market characteristics that form the basis of wage determination. In this thesis, I intend to understand the connection between wage gap and factors including workplace discrimination, education, occupational segregation, and, to uncover the challenges of the Equal Pay movement by identifying the main issues arise around the movement. Specifically, I performed a Twitter-based user generated content analysis (UGC) to extract twitter data with the hashtag #GenderPay and #EqualPay to further understand the issues around the equal pay movement. In the UGC analysis, I built a Latent Dirichlet Allocation (LDA) model to identify top 20 topics in the dataset. I classified the tweets into three categories - positive, negative, and neutral - and plotted two word-clouds. My findings underscore the following two topics: (i) motherhood penalty (ii) racial inequality. The identified topics can be a starting point for future research on pay equity in the work environment as well as provide insights to close the gender inequality problem around the world.



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