Analyzing Twitter Sentiments with Big Data

Sentimental analysis is the process of defining the opinion of the individual by extracting the data. Sentimental analysis is done by collecting the data from variety of resources like internet and social media platforms like (Face book, twitter) and it stored in different formats. The data extracted from these social media platforms can be used for different purposes like prediction, marketing and sentiment analysis. Politicians use sentimental analysis to know how people feel about themselves and their parties. Twitter is a widely used platform for posting comments through short messages. Every year millions or billions of tweets extracted are subjected to sentiment analysis. But handling such a huge amount of unstructured or structured data is a tedious task to take by the traditional storage system (such as RDBMS, Relational Database System). Therefore., we need a tool that can process and analyze this unrelated data. So; we have utilized big data technology to handle different formats of unstructured and structured data from different sources.