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Sentiment analysis of tweets to identify the correlated factors that influence an issue of interest

Social networking sites have become very popular in last few decades. People share or post their opinions or feelings on all the issues rise in society and how those issues are affecting their daily life routine. Twitter is one of these social media site where users express their personal view on different issues. Analysing tweets to understand the sentiments of the public has been interesting problem. In this work we want to explore the mining of tweets to understand correlated issues and their relevance. In this paper we have introduced a technique that applies machine learning algorithm on the collected tweets of some specific event to find out people's feelings about particular issue as well as related issues. The tool gives visualization of sentiment analysis of tweets according to locations. Efficiency of several machine learning algorithms are compared for choosing better algorithm. As a proof of concept we have analysed the recent tweets arising from Aamir Khans statement of Intolerant India, Arvind Kejriwal's ‘OddEven’ formula and ‘Free Basics’ by Facebook.