Does Chatter Really Matter? Dynamics of User-Generated Content and Stock Performance

Seshadri Tirunillai () and Gerard J. Tellis ()
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Seshadri Tirunillai: C.T. Bauer College of Business, University of Houston, Houston, Texas 77204
Gerard J. Tellis: Marshall School of Business, University of Southern California, Los Angeles, California 90089

Marketing Science, 2012, vol. 31, issue 2, 198-215

Abstract: This study examines whether user-generated content (UGC) is related to stock market performance, which metric of UGC has the strongest relationship, and what the dynamics of the relationship are. We aggregate UGC from multiple websites over a four-year period across 6 markets and 15 firms. We derive multiple metrics of UGC and use multivariate time-series models to assess the relationship between UGC and stock market performance.

Volume of chatter significantly leads abnormal returns by a few days (supported by Granger causality tests). Of all the metrics of UGC, volume of chatter has the strongest positive effect on abnormal returns and trading volume. The effect of negative and positive metrics of UGC on abnormal returns is asymmetric. Whereas negative UGC has a significant negative effect on abnormal returns with a short "wear-in" and long "wear-out," positive UGC has no significant effect on these metrics. The volume of chatter and negative chatter have a significant positive effect on trading volume. Idiosyncratic risk increases significantly with negative information in UGC. Positive information does not have much influence on the risk of the firm. An increase in off-line advertising significantly increases the volume of chatter and decreases negative chatter. These results have important implications for managers and investors.

Keywords: user-generated content (UGC); stock returns; online word of mouth; vector autoregression (VAR); computational text processing (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (146)

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