Sentimental analysis on Twitter data using hadoop with spring web MVC

Madhavi Kondapally, Ravikiran Ramaraju, G Ravi

Abstract:

This paper addresses the sentiment analysis on Twitter data, i.e.,
obtaining User sentiments by classifying tweets according to their opinions
positive, negative or neutral. This paper primarily consists of live stream data
generation, process and visualization through GUI based application for the
results. Output will be visualized through Google charts. Opinion tweet results
will be displayed in the form of Pie charts. Twitter is an online micro-blogging
on social-networking platform which allows users to express their ideas. It is a
rapidly expanding service with over 555 million users, generating millions of
tweets per day. We can obtain public sentiment through this data, it is crucial
for many applications such as predicting political elections suppose public
opinion on the prime minister and for obtaining product reviews of firms. The
aim of this project is to find sentiments from the Twitter live streaming data
using Apache flume, Hadoop and visualize the results in the Web application.