University of South Florida (USF) M3 Publishing



Reviews about tourism products in online environments are an important data source for tourism businesses, destination managements and tourists. Tourist reviews online are completely unbiased reviews created voluntarily by tourists. Therefore, important feedback is provided for tourism businesses and destinations in the evaluation of tourism products. Collecting and analyzing tourist comments and transforming them into strategic information will create an important competitive power. Sentiment analysis, which is a sub-field of text mining, is a field of study that analyzes people’s ideas and thoughts about tourism products and services from text-based comments. Sentiment analysis can be applied at the document level, sentence level and aspect-based sentiment levels. In this chapter, sentiment analysis methods are examined by using data collected from online platforms where tourism products are evaluated. Analyzing online tourist reviews using text mining methods will provide important opportunities for stakeholders in the tourism sector. These opportunities can be explained in terms of destination management, tourism businesses and tourists. Understanding and interpreting the destination for destination management will thus provide opportunities for the creation of the brand value and image of the destination. It will also make an important contribution to the determination of tourist needs in the destination and meeting these needs. In terms of tourism businesses, evaluating the products and services they offer to tourists will create an opportunity to manage customer relations by discovering the negative and positive aspects. In addition, tourism businesses will have the opportunity to develop or improve their products and services in order to gain product and price advantage by evaluating their competitors. Tourists will be able to use it to make better travel plans.


After completing this chapter, the student will be able to:

  • Have general information about text mining.
  • Understands text mining methods.
  • Have knowledge about sentiment analysis and understand sentiment analysis methods.
  • Understands how to apply sentiment analysis tools.
  • Apply Aspect-based Sentiment Analysis to tourist comments.
  • Can develop text mining and sentiment analysis applications in RapidMiner.
  • Analyzes the comments written by tourists about touristic products.



Recommended Citation

Ozen, I. A. (2021). Tourism products and sentiment analysis. In C. Cobanoglu, S. Dogan, K. Berezina, & G. Collins (Eds.), Advances in hospitality and tourism information technology (pp. 1–38). USF M3 Publishing. https://www.doi.org/10.5038/9781732127586

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License



To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.