Stock Market Prediction Using Twitter Mood
In the modern times of the information age, the magnitude of social media activity has reached unprecedented levels. Twitter is one such popular online social networking and micro blogging service, which enables hundreds of millions of users share short messages in real time about events worth broad attention expressing public opinion. In this paper, we investigate the relationship between Twitter opinion and stock price movement. Specifically, we wish to see if, and how well sentiment information extracted from twitter can be used to predict future shifts in prices. Stock market forecasting is a popular and important topic in financial and academic studies. Time series analysis is the most common and fundamental method used to perform this task. Tweets related to selected company over the last three months are collected. The result of this experiment shows the significant correlation between the changes in daily stock price and changes in polarity of tweets computed using sentiment analysis of tweets. Keywords Apple, Stock Market Prediction, Twitter, Sentiment Analysis, Regression