Sentiment Analysis of Public Perception Towards Transgender Rights on Twitter

The fight for equal transgender rights is gaining traction in the public eye, but still has a lot of progress to make in the social and legal spheres. Since public opinion is critical in any civil rights movement, this study attempts to identify the most effective methods to elicit public reactions in support of transgender rights. Topic analysis through Latent Dirichlet Allocation is performed on Twitter data, along with polarity sentiment analysis, to track the subjects which gain the most effective reactions over time. Graphing techniques are used in an attempt to visually display the trends in topics. The topic analysis techniques are effective in identifying the positive and negative trends in the data, but the graphing algorithm lacks the ability to comprehensibly display complex data with more dimensionality.