The Implication of Tweet's Distribution by Quantizing Stock Values for Inference in the Indian Financial Market: A Sentiment Analysis Approach

Abstract

The rise of social networking has changed the behavior of the entire world.In these day's most of the people put their opinion in the social media so these allow users to access the real-time data from social networks generating the huge amount of data worthy for sentiment analysis and its future prediction.In this paper, we have proposed a promising approach with the help of twitter's API by collecting the tweets on a daily basis and analyzing them for calculating sentiment out of it. We have proposed here the new method i.e. By quantizing the closing stock values of companies listed in NSE by combining them with sentiment's derived from tweets of the same date with the help of the most powerful NLP tool LING PIPE and calculate the distribution of each tweet. This has proved to be a one of the best method for predicting the sentiment of company present public's mind as a result this sentiment is significant for traders who are interested to invest in that company.