Out of the Closet: Lexicon Based Sentiment Analysis on Tweets about Homosexuality

Social media sites such as Twitter have given a platform to people to express their thoughts even on the most sensitive of topics. In this paper, we analyze tweets which are posted by people who acknowledged their sexuality and shared their friends and families' response publicly. In our experiment, we have used a set of Tweets data with specific hashtags to analyze the response. Context-based topic modeling was used to gather tweets surrounding this topic to get the relevant tweets. The unwanted tweets discovered by the topic model was discarded. The sentiment of these tweets was then extracted using novel methods. The motivation for this process was to find out how their declaration of sexuality was perceived. Unfortunately, homophobia is one of the battles humanity continues to fight.