Big Data Migration and Sentiment Analysis of Real Time Events Using Hadoop Ecosystem

Abstract

Big Data is one of the most trending topics in computer science. We all know that digital data is in unstructured format. The main purpose is to derive real-time data possessed to by different fields. Organization needs a systematic base to manage information and execute most important applications. Currently, opinions and polls that are available are the most vital part in deciding our views which in turn depicts the rate of success or impact of a product. With the stupendous widening of social media, collaborators many a times take to convey their judgement on favoured social media like twitter. Twitter data is exceptionally illuminating, it handovers a challenge for inspection because of its formidable and unorganized type. This work is a rigorous effort to plunge into the hardback domain of executing analysis of people’s sentiment [1] concerning political parties in India and also gets hold of extra pre-processing computations like deletion of repeating tweets. A method is devised wherein the tweets are categorised as positive, neutral and negative tweets [2] which is then represented through a graph which helps in depicting the chances of winning concerning a particular political party.