Sentiment analysis framework organization based on twitter corpus data

Since its inception in 2006, Twitter has gathered millions of users. They post daily tweets about news, events or conversations. These tweets express their opinion about the topic they are discussing. Twitter is a large database of content that can be semantically exploited to extract opinions and based on these opinions to classify the users. This paper presents the organization of a sentiment analysis framework based on Twitter corpus data, including crawling tweets and opinion mining of the tweets, making it easy for its users to create portfolios of trustful Twitter accounts.