Research on stock market prediction has a deep foundation in economic and business research. Recent research into social media has shown that it can be an accurate tool for stock market prediction modeling. This study will continue in this field of research by attempting to determine if stock market volatility can be predicted using Twitter volume data and user metadata. ARCH regression methods are utilized to evaluate time-series data sets of Tweets filtered by 48 separate S&P 500 companies. While the results are for the most part insignificant, the future is bright for social media research in the academia community.
Includes bibliographical references.