Sentiment Analysis for Stock and Share Marketing

Abstract

Sentiment analysis refers to the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information. sentiment analysis aims to determine the attitude of a speaker, writer, or other subject with respect to some topic or the overall contextual polarity or emotional reaction to a document, interaction, or event. This paper will showcase how to perform sentimental analysis on stock/share market twitter data using pig. To begin with, we will be collecting real time tweets from twitter using flume. With the help of AFINN dictionary, we can find positive sentiments from the data which we have dumped into our HDFS/FLUME.