Stock Market Prediction Using Machine Learning and Twitter Sentiment Analysis: An Implementation Survey

Abstract

Sentiment analysis has received a variety of interest in the ultimate decade in particular on the availability of statistics from social media web sites due to this quite a few researchers are showing greater interest on this subject. Many researchers believe that the mood of people or sentiment expressed by using them on social media has an impact on economic markets actions. This paper plans to notice the effect of opinion communicated by means of Twitter on the financial exchange and afterward anticipate the moves of the financial exchange for the next days. For extracting tweets data from Twitter, we will be using Tweepy and for the verification of extracted information, we will use Yahoo Finance. To predict we intend to apply three machine algorithms Autoregressive integrated moving average, long short-term memory, and Linear Regression. The expectation is to apply authentic stock information in relationship with opinion examination of information features and Twitter tweets information, to anticipate the future pace of a stock of interest.