Sentiment Analysis of Financial News

Sentiment analysis is a subdiscipline covered under data mining and computational semantics. It refers to the comprehension of gathered data that is procured from sentiment rich sources like news, social media sites, reviews, and so forth. In the current era where data is becoming increasingly voluminous and yet crucial to all businesses, manual analysis of data does not remain viable in this fast-moving world. Thus, it is necessary to make use of artificial intelligence and datamining techniques. Amongst several variables, a key determinant that result in the fluctuation in stock prices is the gains or losses incurred by a company. As most traders get their information from news, it makes news as a core influential factor to forecast change in the stock market. This study focuses on sentiment classification and shows its effect on the change in stock market prices. It generates investing insight by applying sentiment analysis using VADER (Valence Aware Dictionary and Sentiment Reasoner) tool on some of the most liquid stocks.

I. Introduction

The stock market is a significant component of the economy of a nation. It performs a crucial role in the growth of a business and trade of a country. Thus, it greatly influences the economy of the nation and with the advent of globalization now has a global effect. Therefore, all parties linked directly or indirectly to the stock market maintain a close watch on it. Sentiment analysis of news which is unstructured data can help in predicting market changes [1–2].