| Sumario: | With the increase in advancement in Artificial Intelligence and Data Mining, sentiment analysis is a hot topic. Also, social media is getting more coverage. Public and private opinions on a wide range of topics are constantly shared and distributed through a variety of social media platforms. Twitter is a popular social media platform. Twitter provides businesses with a quick and easy way to assess their consumers' views on issues that are vital to their success in the marketplace. It solves the underlying problem of sentiments that is generally lost in between tweets and retweets. This would improve understanding of the underlying context and the sentiment behind the particular tweet and gain clarity on the subject. We achieve this strategy, with techniques such as Data Mining and Natural Language Processing for extractCreating a sentiment analysis software is a method for measuring consumers' expectations computationally. This paper describes the development of a sentiment analysis that extracts a large number of tweets. Thus, we arrive at a conclusion where we expect to achieve an attractive accuracy rate using this technique.
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