Sentiment Analysis on Twitter Using Streaming API

Abstract

In general, opinion mining has been used to know about what people think and feel about their products and services in social media platforms. Millions of users share opinions on different aspects of life every day. Spurred by that growth, companies and media organizations are increasingly seeking way to mine information. It requires efficient techniques to collect a large amount of social media data and extract meaningful information from them. This paper aims to provide an interactive automatic system which predicts the sentiment of the review/tweets of the people posted in social media using hadoop, which can process the huge amount of data. Till now, there are few different problems predominating in this research community, namely, sentiment classification, feature based classification and handling negations. A precise method is used for predicting sentiment polarity, which helps to improve marketing strategies. This paper deals with the challenges that appear in the process of Sentiment Analysis, real time tweets areconsidered as they are rich sources of data for opinion mining and sentiment analysis. This paper focus on Sentiment analysis, Feature based Sentiment classification and Opinion Summarization. The main objective of this paper is to perform real time sentimental analysis on the tweets that are extracted from the twitter and provide time based analytics to the user.