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Marketing Research: The Role Of Sentiment Analysis

Author

Listed:
  • Meena Rambocas

    (Department of Management Studies, The University of the West Indies (St. Augustine Campus))

  • João Gama

    (Laboratory of Artificial Intelligence andDecision Support & Faculty of Economics University of Porto)

Abstract

This article promotes sentiment analysis as an alternative research technique for collecting and analyzing textual data on the internet. Sentiment analysis is a data mining technique that systematically evaluates textual content using machine learning techniques. As a research method in marketing, sentiment analysis presents an efficient and effective evaluation of consumer opinions in real time. It allows data collection and analysis from a very large sample without hindrances, obstructions and time delays. Through sentiment analysis, marketers collect rich data on attitudes and opinion in real time, without compromising reliability, validity and generalizability. Marketers also gather feedback on attitudes and opinions as they occur without having to invest in lengthy and costly market research activities. The paper proposes sentiment analysis as an alternative technique capable of triangulating qualitative and quantitative methods through innovative real time data collection and analysis. The paper concludes with the challenges marketers can face when using this technique in their research work.

Suggested Citation

  • Meena Rambocas & João Gama, 2013. "Marketing Research: The Role Of Sentiment Analysis," FEP Working Papers 489, Universidade do Porto, Faculdade de Economia do Porto.
    • Handle: RePEc:por:fepwps:489
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    File URL: http://www.fep.up.pt/investigacao/workingpapers/wp489.pdf
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    References listed on IDEAS

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    1. Gruen, Thomas W. & Osmonbekov, Talai & Czaplewski, Andrew J., 2006. "eWOM: The impact of customer-to-customer online know-how exchange on customer value and loyalty," Journal of Business Research, Elsevier, vol. 59(4), pages 449-456, April.
    2. Kaplan, Andreas M. & Haenlein, Michael, 2010. "Users of the world, unite! The challenges and opportunities of Social Media," Business Horizons, Elsevier, vol. 53(1), pages 59-68, January.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Ali B. Mahmoud & Dieu Hack-Polay & Nicholas Grigoriou & Iris Mohr & Leonora Fuxman, 2021. "A generational investigation and sentiment and emotion analyses of female fashion brand users on Instagram in Sub-Saharan Africa," Journal of Brand Management, Palgrave Macmillan, vol. 28(5), pages 526-544, September.
    2. Saba Resnik & Mateja Kos Koklič, 2018. "User-Generated Tweets about Global Green Brands: A Sentiment Analysis Approach," Tržište/Market, Faculty of Economics and Business, University of Zagreb, vol. 30(2), pages 125-145.
    3. Kim, Jikyung (Jeanne) & Dong, Hang & Choi, Jeonghye & Chang, Sue Ryung, 2022. "Sentiment change and negative herding: Evidence from microblogging and news," Journal of Business Research, Elsevier, vol. 142(C), pages 364-376.
    4. Vagianos Dimitrios & Koutsoupias Nikos, 2021. "Framing Coworking Spaces Marketing Strategies via Social Media Indices," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 25(2), pages 1-14, June.
    5. Dimitrios Kydros & Maria Argyropoulou & Vasiliki Vrana, 2021. "A Content and Sentiment Analysis of Greek Tweets during the Pandemic," Sustainability, MDPI, vol. 13(11), pages 1-21, May.
    6. David-Florin Ciocodeică & Raluca-Giorgiana (Popa) Chivu & Ionuț-Claudiu Popa & Horia Mihălcescu & Gheorghe Orzan & Ana-Maria (Dumitrache) Băjan, 2022. "The Degree of Adoption of Business Intelligence in Romanian Companies—The Case of Sentiment Analysis as a Marketing Analytical Tool," Sustainability, MDPI, vol. 14(12), pages 1-20, June.

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    More about this item

    Keywords

    Sentiment analysis; Machine leaning; Marketing research; Triangulation; Qualitative research; Quantitative research;
    All these keywords.

    JEL classification:

    • M10 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - General
    • M30 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - General
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing
    • M39 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Other

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