Network Structure and Predictive Power of Social Media in the Bitcoin Market
36 Pages Posted: 9 Jan 2017 Last revised: 4 Jul 2018
Date Written: June 2018
Following the recent discovery of social media’s predictive power in stock markets, we advance this literature by investigating whether the network structure of social media discussions can help distinguish between value-relevant information and noise. Using data from the Bitcoin market, we provide empirical evidence that less cohesive social media discussion networks are more accurate in predicting future returns. We reassure the findings with several trading simulations. Whether short selling is allowed or not, trading strategies based on sentiments weighted by discussion network cohesion yield two to three times the returns generated by random trading or strategies based on equally-weighted sentiments.
Keywords: financial technology, social media analytics, network structure, Bitcoin, prediction, topic modeling
Suggested Citation: Suggested Citation