The relationship between twitter and stock prices. Evidence from the US technology industry

Abstract

The widespread use of social media and the amplified interest have enormously increased the amount of data available on these platforms. This paper aims at exploring the use of social media as a tool for investing, verifying the relationship with stock prices. Rather than focusing on a market index, we analyze the technology industry in the U.S., to understand if this methodology can be used not only to capture the wider sentiment of the market, but also to invest in a single stock. OLS models are applied to verify the predictive power of Twitter and traditional media on the particular sample. The results prove that prediction markets manage to effectively pool decentralized information better alternative sources. Findings indicate higher association between the stock price of companies and high social media coverage than that with low coverage.