SENTIMENT ANALYSIS: AN APPROACH TO OPINION MINING FROM TWITTER DATA USING R

Abstract

Opinion mining also termed as sentiment analysisis basically utillized to implement anautomated algorithm to analyze and classify opinion.If we are interested to get the idea, the extent to which the Indian citizen likes or dislikes money demonetization or for instance consider a product marketer who on his present company market image, would like to decide upon, launching of his new product. A film celebrity who would like to judge his or her present popularity so as to decide on the perfect time to launch his or her new movie, for any of such case an obvious solution would require analysis of opinion from a random sample of people. For such public opinion measurement, various survey tools and techniques are available. With the sudden increase in text based social media, lump of people simulcast their point of view and ideas on a large range of issues. We can study this data available from public to conclude population attitudes to understand the current trends of the market. This study presents a very easy, costand time effective approach that expose the opinions of much larger public (not bounded by any geographical boundaries) which otherwise would have been not possible. The study presents an exhaustive study on the efficiency of R language in opinion mining and how opinion data can be extracted from twitter database. Extorting the opinion of people from social media text provides a rich and interesting context of database to analysis.