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Whose and What Chatter Matters? The Effect of Tweets on Movie Sales

Author

Listed:
  • Huaxia Rui

    (University of Texas)

  • Yizao Liu

    (University of Connecticut)

  • Andrew Whinston

    (University of Texas)

Abstract

Social broadcasting networks such as Twitter in the U.S. and "Weibo" in China are transforming the way online word of mouth (WOM) is disseminated and consumed in the digital age. In the present study, we investigated whether and how Twitter WOM affects movie sales by estimating a dynamic panel data model using publicly available data and well-known machine learning algorithms. We found that chatter on Twitter does matter; however, the magnitude and direction of the effect depends on whom the WOM is from and what the WOM is about. Measuring Twitter users' in uence by how many followers they had, we found that the effect of WOM from more in fluential users is signifcantly larger than that from less in uential users. In support of some recent findings about the importance of WOM valence on product sales, we also found that positive Twitter WOM increases movie sales, whereas negative WOM decreases them. Interestingly, we found that the strongest effect on movie sales comes from those tweets in which the authors expressed their intention to watch a certain movie. We attribute this finding to the dual effects of such intention tweets on movie sales: the direct effect through the WOM author's own purchase behavior, and the indirect effect through either the awareness effect or the persuasive effect of the WOM on its recipients. Our findings provide new perspectives to understand the effect of WOM on product sales and have important managerial implications. For example, our study reveals the potential values of monitoring people's intentions and sentiments on Twitter and identifying in uential users for companies wishing to harness the power of social broadcasting networks.

Suggested Citation

  • Huaxia Rui & Yizao Liu & Andrew Whinston, 2012. "Whose and What Chatter Matters? The Effect of Tweets on Movie Sales," Working Papers 08, University of Connecticut, Department of Agricultural and Resource Economics, Charles J. Zwick Center for Food and Resource Policy.
  • Handle: RePEc:zwi:wpaper:08
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    File URL: http://www.zwickcenter.uconn.edu/documents/WPNo.8.pdf
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    References listed on IDEAS

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    1. Dhar, Vasant & Chang, Elaine A., 2009. "Does Chatter Matter? The Impact of User-Generated Content on Music Sales," Journal of Interactive Marketing, Elsevier, vol. 23(4), pages 300-307.
    2. De Vany, Arthur & Walls, W David, 1996. "Bose-Einstein Dynamics and Adaptive Contracting in the Motion Picture Industry," Economic Journal, Royal Economic Society, vol. 106(439), pages 1493-1514, November.
    3. David Godes & Dina Mayzlin, 2004. "Using Online Conversations to Study Word-of-Mouth Communication," Marketing Science, INFORMS, vol. 23(4), pages 545-560, June.
    4. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Oxford University Press, vol. 58(2), pages 277-297.
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    More about this item

    Keywords

    Twitter; word-of-mouth; dynamic panel data;
    All these keywords.

    JEL classification:

    • M3 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables

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