Wisdom of Crowds: Cross-sectional Variation in the Informativeness of Third-Party-Generated Product Information on Twitter

Abstract

This paper examines whether third-party-generated product information on Twitter, once aggregated at the firm level, is predictive of firm-level sales, and if so, what factors determine the cross-sectional variation in the predictive power. First, the predictive power of Twitter comments increases with the extent to which they fairly represent the broad customer response to products and brands. The predictive power is greater for firms whose major customers are consumers rather than businesses. Second, the word-of-mouth effect of Twitter comments is greater when advertising is limited. Third, a detailed analysis of the identity of the tweet handles provides the additional insights that the predictive power of the volume of Twitter comments is dominated by “the wisdom of crowds,” whereas the predictive power of the valence of Twitter comments is largely attributable to expert comments. Furthermore, Twitter comments not only reflect upcoming sales, but also capture an unexpected component of sales growth.

Keywords: product information, social media, fundamental analysis, information processing, twitter, word of mouth, sales forecasting

JEL Classification: D83, G14, M41, O33