Abstract
This paper models stock manipulations where investors interact via social network communications. We propose a novel noise index in social media platforms. The model predicts that high volumes of social media noise significantly increase probability of success, profitability for manipulators as well as heighten trading volume of manipulated stocks. In addition, manipulation profitability increases with respect to the number of followers in social media posts mentioned the manipulated stock. Empirical investigations, based on over 3,800 U.S. small-cap stocks during January 2010 to 2018 December, confirm the theoretical predictions and hypotheses. Our paper demonstrates an urgent need for monitoring social media platforms in safeguarding financial market efficiency.