Brazilian social mood: The political dimension of emotion

Abstract

Brazil faces a major economic and political crisis. Millions of people joined anti-government protests across the country. Social media sites are a way for some people to vent their emotions without feeling self-conscious. Thus, emotion mining on social media can be viewed as effective tool to conduct Presidential approval rating. This research aims to automatically recognize emotion in texts extracted from social media in Brazilian Portuguese (PT-BR). The ultimate goal is knowing how emotions influence a writer of a text in choosing certain words and/or other linguistic elements. In this research, we perform keyword based approaches using affect lexicon and a Support Vector Machine and Naïve Bayes algorithms.