We argue that affect plays an important role in pricing models for stocks. We exploit a novel dataset of opinions shared on a social media platform to quantify the affect associated with stocks. We show that individual stock opinions collected from a social media platform systematically differ from other risk factors and qualify as an additional factor in asset pricing models. Stocks with high affect feature smaller risk premiums.