Social Media Network Structure and Stock Market Reactions to Buy Recommendations Issued by Social Media Analysts
Abstract
This study investigates how social media network structure influences short-term stock market reactions to buy recommendations issued by self-identified social media analysts (SMAs) within online retail investor communities. Consistent with social learning theories-and in contrast to social utility theories-we find that communities with lower network cohesion experience more positive short-term market reactions to buy recommendations. However, this negative relation diminishes at higher levels of network cohesion. Further supporting the social learning theories, the impact of network cohesion is more pronounced for SMAs with higher recommendation accuracy. In line with behavioral finance theories, we also find the effect of network cohesion to be stronger for stocks facing greater limits to arbitrage. Our exploratory analysis suggests that part of the initial price reaction reflects investor overreaction, as indicated by subsequent price reversals.