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What Role Do Emotions Play for Brands in Online Customer Reviews?

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Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 261))

Abstract

The field of mining unstructured data has been growing rapidly in business intelligence. An area of application represent online reviews where customers interact socially to share opinions towards brands. Thereby, exchanged emotions play a dominant role, which poses a challenge for brand managers to understand the emotional attitude in customer’s reviews. We develop a text-mining method that extracts information about emotions from customers’ product reviews. We cast the underlying analysis of emotions as a binary classification problem, by using features extracted with the help of a psychologically well-grounded emotion lexicon. Based on this, we identify for various brands, which emotion features are important in reviews that are perceived as helpful (and thus more influential) by customers. We have conducted an empirical investigation with a large, publicly available data set from Amazon. Among other insights, our findings can determine the importance of various emotions for different brands throughout several product categories.

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Notes

  1. 1.

    We follow the assumption that, as is typical in many e-commerce sites, customers can vote a review as helpful or not helpful.

  2. 2.

    Please note that for a better overview, we have arranged the brands from adidas Group of Fig. 6 in the same order as displayed in the gray box in Fig. 5.

References

  1. Anderson, E.W., Fornell, C., Lehmann, D.R.: Customer satisfaction, market share, profitability: findings from Sweden. J. Market. 58, 53–66 (1994)

    Article  Google Scholar 

  2. Bougie, R., Pieters, R., Zeelenberg, M.: Angry customers don’t come back, they get back: The experience and behavioral implications of anger and dissatisfaction in services. J. Acad. Mark. Sci. 31(4), 377–393 (2003)

    Article  Google Scholar 

  3. Breiman, L.: Random forests. Mach. Learn. 45(1), 5–32 (2001)

    Article  Google Scholar 

  4. Caruana, R., Niculescu-Mizil, A.: An empirical comparison of supervised learning algorithms. In: Proceedings of the 23rd International Conference on Machine Learning, pp. 161–168. ACM (2006)

    Google Scholar 

  5. Cho, Y., Im, I., Hiltz, R., Fjermestad, J.: An analysis of online customer complaints: implications for web complaint management. In: Proceedings of the 35th Annual Hawaii International Conference on System Sciences, HICSS, pp. 2308–2317. IEEE (2002)

    Google Scholar 

  6. Dick, A.S.: Customer loyalty: toward an integrated conceptual framework. J. Acad. Market. Sci. 22(2), 99–113 (1994)

    Article  Google Scholar 

  7. Duffy, N., Hooper, J.: Passion Branding: Harnessing the Power of Emotion to Build Strong Brands. Wiley, New York (2004)

    Google Scholar 

  8. Ittner, C.D., Larcker, D.F.: Are nonfinancial measures leading indicators of financial performance? An analysis of customer satisfaction. J. Account. Res. 36, 1–35 (1998)

    Article  Google Scholar 

  9. Kapferer, J.-N.: The New Strategic Brand Management: Advanced Insights and Strategic Thinking. Kogan page publishers, London (2012)

    Google Scholar 

  10. Martin, L., Sintsova, V., Pearl, P.: Are influential writers more objective? An analysis of emotionality in review comments. In: Proceedings of the Companion Publication of the 23rd International Conference on World Wide Web Companion, pp. 799–804. International World Wide Web Conferences Steering Committee (2014)

    Google Scholar 

  11. Maynard, D., Bontcheva, K., Rout, D.: Challenges in developing opinion mining tools for social media. In: Proceedings of the@ NLP can u tag #usergeneratedcontent, pp. 15–22 (2012)

    Google Scholar 

  12. McAuley, J., Leskovec, J.: Hidden factors and hidden topics: understanding rating dimensions with review text. In: Proceedings of the 7th ACM Conference on Recommender Systems, pp. 165–172. ACM (2013)

    Google Scholar 

  13. Saif, M.M., Peter, D.T.: Crowdsourcing a word-emotion association lexicon. Comput. Intell. 29(3), 436–465 (2013)

    Article  Google Scholar 

  14. David, W.N., Jeffrey, F.D., VanDe Velde, J.: Producing customer happiness: the job to do for brand innovation. Des. Manage. Rev. 21(3), 6–15 (2010)

    Article  Google Scholar 

  15. Pang, B., Lee, L.: A sentimental education: sentiment analysis using subjectivity summarization based on minimum cuts. In: Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics, p. 271. Association for Computational Linguistics (2004)

    Google Scholar 

  16. Plutchik, R.: A general psychoevolutionary theory of emotion. In: Theories of Emotion, vol. 1 (1980)

    Google Scholar 

  17. Roberts, K.: Lovemarks: the future beyond brands. LA COMUNICACIÓN DE LAS MARCAS, p. 35 (2005)

    Google Scholar 

  18. Rossiter, J., Bellman, S.: Emotional branding pays off: how brands meet share of requirements through bonding, companionship, and love. Faculty of Commerce-Papers (Archive), pp. 291–296 (2012)

    Google Scholar 

  19. Klaus, R.: What are emotions? And how can they be measured? Soc. Sci. Inf. 44(4), 695–729 (2005)

    Article  Google Scholar 

  20. Amy, K., Ruth, N.B.: The effect of customers’ emotional responses to service failures on their recovery effort evaluations and satisfaction judgments. J. Acad. Mark. Sci. 30(1), 5–23 (2002)

    Article  Google Scholar 

  21. Thomson, M., Deborah, J.M., Whan Park, C.: The ties that bind: measuring the strength of consumers emotional attachments to brands. J. Consum. Psychol. 15(1), 77–91 (2005)

    Article  Google Scholar 

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Correspondence to Armin Felbermayr .

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Felbermayr, A., Nanopoulos, A. (2016). What Role Do Emotions Play for Brands in Online Customer Reviews?. In: Řepa, V., Bruckner, T. (eds) Perspectives in Business Informatics Research. BIR 2016. Lecture Notes in Business Information Processing, vol 261. Springer, Cham. https://doi.org/10.1007/978-3-319-45321-7_21

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