Emotte: Uma Ferramenta De Análise de Sentimentos para o Twitter - Malheiros, Yuri (Anais Estendidos do Simpósio Brasileiro de Sistemas Multimídia e Web (WebMedia), 2014)
Twitter has hundreds of millions users sending messages (tweets) and expressing their opinions about a myriad of subjects, for instance, what they think about a certain product, or if they liked or not a movie, or their reactions during a soccer game. This massive amount of messages carrying opinions about di erent things could be valuable for business and institutions. Because, it is possible to monitor many people in real time to obtain what they are expressing in their messages in an automatic, fast, and authentic way. In this work, I present Emotte, a tool to analyze sentiment in messages sent to Twitter using machine learning and natural language processing algorithms. The tool monitors the tweets according to queries, classify their sentiments, and display the results using a chart. Thus, someone using Emotte can compare over time the evolution of the opinion of the Twitter users about certain subjects.