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Do Emotions Matter? Exploring The Distribution Of Emotions In Online Product Reviews

Author

Listed:
  • Rahat Ullah

    (Korea Advanced Institute of Science and Technology (KAIST))

  • Wonjoon Kim

    (Korea Advanced Institute of Science and Technology (KAIST))

  • Naveen C. Amblee

    (Indian Institute of Management Kozhikode)

  • Hyunjong Lee

    (Korea Advanced Institute of Science and Technology (KAIST))

  • Alice Oh

    (Korea Advanced Institute of Science and Technology (KAIST))

Abstract

Word-of-mouth (WOM) in the form of online customer reviews has received considerable attention by practitioners and academics. Prior literature has focused more on the understanding of the phenomenon using the frequency or overall rating/valence information of WOM such as the causal effect on consumer choice, distribution pattern of WOM, and its product type-dependency, while questions on how firms can potentially use or design online WOM platforms and benefit from it based on the content of WOM are still open, and needs more attention from researchers. In addition, an important antecedent for the generation of word-of-mouth is a strong emotional response, which in turn triggers the consumer to post a customer review online. However, only a limited number of studies to date have actually examined the content of reviews for their emotional content. To fill this gap, we analyzed the emotional content of a large number of online product reviews using Natural Language Processing (NLP) methods. We found that more extreme reviews have a greater proportion of emotional content than less extreme reviews, revealing a bimodal distribution of emotional content, thereby empirically validating a key assumption that underpins much of the extant literature on online WOM. In addition, we found reviews have a greater proportion of positive emotional content within positive extreme ratings as compared to negative emotional content within negative extreme ratings which is a major factor in online WOM generation. Investigating further, we did find that there is a difference in the emotional content of reviews between search and experience goods in the early stages of product launch. However, interestingly, we find that these differences disappear over time as the addition of reviews reduces the information asymmetry gap. This provides important evidence to the widely held notion that on the Internet, all goods become search goods. Our findings suggest important managerial implications regarding product development, advertisement, and platform design using WOM content.

Suggested Citation

  • Rahat Ullah & Wonjoon Kim & Naveen C. Amblee & Hyunjong Lee & Alice Oh, 2014. "Do Emotions Matter? Exploring The Distribution Of Emotions In Online Product Reviews," Working papers 156, Indian Institute of Management Kozhikode.
    • Handle: RePEc:iik:wpaper:156
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    References listed on IDEAS

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    1. Derbaix, Christian & Pham, Michel T., 1991. "Affective reactions to consumption situations: A pilot investigation," Journal of Economic Psychology, Elsevier, vol. 12(2), pages 325-355, June.
    2. David Godes & Dina Mayzlin & Yubo Chen & Sanjiv Das & Chrysanthos Dellarocas & Bruce Pfeiffer & Barak Libai & Subrata Sen & Mengze Shi & Peeter Verlegh, 2005. "The Firm's Management of Social Interactions," Marketing Letters, Springer, vol. 16(3), pages 415-428, December.
    3. Derbaix, Christian & Vanhamme, Joelle, 2003. "Inducing word-of-mouth by eliciting surprise - a pilot investigation," Journal of Economic Psychology, Elsevier, vol. 24(1), pages 99-116, February.
    4. Chrysanthos Dellarocas, 2003. "The Digitization of Word of Mouth: Promise and Challenges of Online Feedback Mechanisms," Management Science, INFORMS, vol. 49(10), pages 1407-1424, October.
    5. John G. Lynch , Jr. & Dan Ariely, 2000. "Wine Online: Search Costs Affect Competition on Price, Quality, and Distribution," Marketing Science, INFORMS, vol. 19(1), pages 83-103, April.
    6. Anindya Ghose & Panagiotis G. Ipeirotis & Beibei Li, 2012. "Designing Ranking Systems for Hotels on Travel Search Engines by Mining User-Generated and Crowdsourced Content," Marketing Science, INFORMS, vol. 31(3), pages 493-520, May.
    7. Nelson, Phillip, 1970. "Information and Consumer Behavior," Journal of Political Economy, University of Chicago Press, vol. 78(2), pages 311-329, March-Apr.
    8. Klein, Lisa R., 1998. "Evaluating the Potential of Interactive Media through a New Lens: Search versus Experience Goods," Journal of Business Research, Elsevier, vol. 41(3), pages 195-203, March.
    9. Xinxin Li & Lorin M. Hitt, 2008. "Self-Selection and Information Role of Online Product Reviews," Information Systems Research, INFORMS, vol. 19(4), pages 456-474, December.
    10. Darby, Michael R & Karni, Edi, 1973. "Free Competition and the Optimal Amount of Fraud," Journal of Law and Economics, University of Chicago Press, vol. 16(1), pages 67-88, April.
    11. David Godes & Dina Mayzlin, 2004. "Using Online Conversations to Study Word-of-Mouth Communication," Marketing Science, INFORMS, vol. 23(4), pages 545-560, June.
    12. Dellarocas, Chrysanthos, 2003. "The Digitization of Word-of-mouth: Promise and Challenges of Online Feedback Mechanisms," Working papers 4296-03, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    13. Mano, Haim & Oliver, Richard L, 1993. "Assessing the Dimensionality and Structure of the Consumption Experience: Evaluation, Feeling, and Satisfaction," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 20(3), pages 451-466, December.
    14. Gupta, Pranjal & Harris, Judy, 2010. "How e-WOM recommendations influence product consideration and quality of choice: A motivation to process information perspective," Journal of Business Research, Elsevier, vol. 63(9-10), pages 1041-1049, September.
    15. Luís Cabral & Ali Hortaçsu, 2010. "The Dynamics Of Seller Reputation: Evidence From Ebay," Journal of Industrial Economics, Wiley Blackwell, vol. 58(1), pages 54-78, March.
    16. Chrysanthos Dellarocas & Charles A. Wood, 2008. "The Sound of Silence in Online Feedback: Estimating Trading Risks in the Presence of Reporting Bias," Management Science, INFORMS, vol. 54(3), pages 460-476, March.
    17. Richins, Marsha L, 1997. "Measuring Emotions in the Consumption Experience," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 24(2), pages 127-146, September.
    18. Westbrook, Robert A & Oliver, Richard L, 1991. "The Dimensionality of Consumption Emotion Patterns and Consumer Satisfaction," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 18(1), pages 84-91, June.
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