A Survey on Opinion Mining on Twitter Data: Tasks, Approaches, Applications and Challenges for Sentimental Analysis

Abstract

-Social media produces huge amounts of data every minute, which is caused by its conventional implementation over the past years. Modernization in the industry have facilitated new ways of communications between people and created many business prospects. Big Data in social media need efficient and sophisticated processing technologies. Rationale of data mining analyses is to discover valuable patterns and insights from Twitter data. In today's world, Social Networking websites like twitter, Facebook, tumbler, etc plays a very significant role. Twitter is a micro-blogging which provides tremendous amount of data which can be used for various applications of sentimental analysis like predictions, reviews, elections, marketing etc. Also for a business to execute successfully it is supportive to identify the opinion viewpoints or reviews of the consumers and make amendments in the tactics and services accordingly. Similarly for the consumers it is very valuable to distinguish about the eminence of the products and services in advance. Sentimental Analysis also called opinion mining is a process of extracting information from large amounts of data and classifies them into different classes called sentiments. Opinion mining is a technique of refining the information and revising the emotions associated with a exacting review and consequently discovering the polarity of the review. In this paper, a study on different perception and move towards of Twitter data analysis performed in recent years by means of opinion mining is prepared by taking into consideration the words, retweets, hash tags and emotions.