An Empirical Study of the Financial Community Network on Twitter

Abstract

Twitter, one of the several major social media platforms, has been identified as an influential factor to financial markets by multiple academic and professional publications in recent years. The motivation of this study hinges on the growing popularity of the use of social media and the increasing prevalence of its influence among the financial investment community. This paper presents an empirical evidence of a financial community in Twitter in which users’ interests align with the financial market. From a large-scale data gathering effort using Twitter API, we establish a methodology in extracting relevant Twitter users to form the financial community, and we present empirical findings of its network characteristics. We find that this financial community behaves similarly to a small-world network, and we further identify a group of critical nodes and analyze their influence within the financial community based on several network centrality measures. Moreover, we document that the sentiment extracted from tweet messages of these critical nodes is significantly correlated with the Dow Jones Industrial Index price and volatility series. By forming a financial community within the Twitter universe, we argue that the critical Twitter users within the financial community provide a better proxy between social sentiment and financial market movement. Hence, sentiment extracted from these critical nodes provides a more robust predictor of financial markets than the general social sentiment.

Keywords: Twitter, Financial market, Sentiment analysis, Network analysis, Financial community

JEL Classification: G1, C2