Abstract

Sentiment analysis refers to the application for processing natural language, text analysis, computational linguistics, and biometrics to methodically recognize, extract, quantify, and learn affective states and subjective information. Twitter, being one among several popular social media platforms, is a place where people often choose to express their emotions and sentiments about a brand, a product or a service. Analyzing sentiments for tweets is very helpful in determining people’s opinion as positive, negative or neutral. This paper evaluates the people’s sentiment about a person, trend, product or brand. Twitter API is used to access the tweets directly from twitter and build a sentiment classification for the tweets. The outcome of the analysis is depicted for positive, negative and neutral remarks about their opinions using visualization techniques such as histogram and Pie chart.

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