earticle

영어

Social media websites have emerged as one of the platforms to raise users’ opinions and influence the way any business is commercialized. Opinion of people matters a lot to analyze how the propagation of information impacts the lives in a large-scale network like Twitter Sentiment analysis of the tweets determine the polarity and inclination of vast population towards specific topic, item or entity. These days, the applications of such analysis can be easily observed during public elections, movie promotions, brand end. In this project, we exploited the fast and in memory computation framework 'Apache Spark' to extract live tweets and perform sentiment analysis. The primary aim is to provide a method for analyzing sentiment score in noisy twitter streams. This paper reports on the design of a sentiment analysis, extracting vast number of tweets. Results classify user's perception via tweets into positive and negative. Secondly, we discuss various techniques to carryout sentiment analysis on twitter data in detail.