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Utilizing text-mining to explore consumer happiness within tourism destinations

Author

Listed:
  • Garner, Benjamin
  • Thornton, Corliss
  • Luo Pawluk, Anita
  • Mora Cortez, Roberto
  • Johnston, Wesley
  • Ayala, Cesar

Abstract

Under growing pressure to demonstrate its societal value, marketing research has the opportunity to focus more on increasing our understanding of consumer happiness. The present research uses topic modeling to interpret and categorize comments from Yelp.com reviews about travel dimensions. In addition, sentiment analysis was used to capture the number of positive and negative words in each review. The data analysis is used to extract and explore the dominant consumer emotions surrounding travel. This research contributes to the practice of marketing and society more broadly by providing an understanding of how memorable experiences are shaped in the travel context and also by demonstrating how machine learning (text mining) can help better understand concepts relating to consumer happiness and well-being.

Suggested Citation

  • Garner, Benjamin & Thornton, Corliss & Luo Pawluk, Anita & Mora Cortez, Roberto & Johnston, Wesley & Ayala, Cesar, 2022. "Utilizing text-mining to explore consumer happiness within tourism destinations," Journal of Business Research, Elsevier, vol. 139(C), pages 1366-1377.
    • Handle: RePEc:eee:jbrese:v:139:y:2022:i:c:p:1366-1377
    DOI: 10.1016/j.jbusres.2021.08.025
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    References listed on IDEAS

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    Cited by:

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    4. Wei Yang & Qiuxia Chen & Yanyue Dao & Xiaoting Huang & Weifang Shao, 2022. "Ecological Civilization and High-Quality Development: Do Tourism Industry and Technological Progress Affect Ecological Economy Development?," IJERPH, MDPI, vol. 20(1), pages 1-25, December.
    5. Oetzel, Sebastian & Graf, Denise, 2023. "Fragen oder Zuhören? Ein Vergleich von Kundenbefragungen und User Generated Content," PraxisWISSEN Marketing: German Journal of Marketing, AfM – Arbeitsgemeinschaft für Marketing, vol. 8(01/2023), pages 91-107.

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