Tweet-level data from a social media platform reveals low average accuracy and high dispersion in the quality of advice by financial influencers, or “finfluencers”: 28% of finfluencers are skilled, generating 2.6% monthly abnormal returns, 16% are unskilled, and 56% have negative skill (“antiskill”) generating -2.3% monthly abnormal returns. Consistent with homophily shaping finfluencers’ social networks, antiskilled finfluencers have more followers and more influence on retail trading than skilled finfluencers. The advice by antiskilled finfluencers creates overly optimistic beliefs most times and persistent swings in followers’ beliefs. Consequently, finfluencers cause excessive trading and inefficient prices such that a contrarian strategy yields 1.2% monthly out-of-sample performance.

We identify a new dimension of cross-firm linkages by exploring the social connectedness between firms' geographical locations. Industry peers located in regions with strong social ties tend to adopt similar strategies and exhibit strong co-movements in both fundamentals and returns. However, this information is not immediately reflected in stock prices and can be exploited using information contained in social peer returns (SPFRET). The predictability of SPFRET lasts for up to a year and forecasts future earnings surprises, analysts' forecast errors, and returns around earnings announcements. The effect is particularly strong for low-visibility firms and those located outside of industry clusters.

Expert networks provide investors with in-depth discussions with subject matter experts. Expert call demand is higher for younger, technology-oriented firms and those with greater intangible assets, consistent with demand for information on hard-to-value firms. Expert calls are more (less) likely to emphasize technology and operational (financial) topics relative to earnings calls. We find that expert call volume is associated with hedge fund position changes and greater price efficiency. The relation is asymmetric, with call volume preceding hedge fund sales, greater short interest, and negative firm performance. The evidence suggests that expert networks help investors discern complicated bad news.