A Framework for Social Network Sentiment Analysis Using Big Data Analytics

Abstract

Traditionally, surveys were used as one of the major methods for finding out the opinion of a group of people about a particular topic. However, over the last two decades with the proliferation of Web to the social media sites such as Twitter, Facebook, and Tumblr, social media are increasingly becoming the platform of choice for people to express their views or opinions. With an account of over two billion users, social media provides a major source for gathering people moods and opinions. Several public and private organizations, such as Government and companies, are attempting to exploit the expressed preferences, opinions, and attitudes regarding politics, commercial products and other matters of personal importance for a competitive edge. One of the efficient ways to get this information is by performing sentiment analysis on these electronic repositories. With the data being ubiquitous, the bottlenecks here are processing speed, storage, and time, which are involved with the traditional storage system. So to deal with the data processing of these massive amounts of data, some special tools and techniques are offered by Big Data framework.