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Sentiment Analysis for Tourism

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Big Data and Innovation in Tourism, Travel, and Hospitality

Abstract

Sentiment analysis software is a key component of tourism big data research for its ability to detect positive and negative opinions in text. This supports large-scale analyses of the key affective dimension of reviews and social web posts about tourism venues and experiences. Sentiment analysis is fast and reasonably accurate, enabling patterns to be mined from large numbers of texts that would not be evident to experts reading those texts, such as differences between genders or venues in the aspects of destinations that are liked. This chapter reviews the main sentiment analysis approaches with a focus on practical descriptions of how the methods work and how they can be applied. The chapter also illustrates the value of sentiment analysis for tourism research.

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Authors and Affiliations

  1. Statistical Cybermetrics Research Group, University of Wolverhampton, Wolverhampton, UK

    Mike Thelwall

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  1. Mike Thelwall
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Correspondence to Mike Thelwall .

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Editors and Affiliations

  1. School of Management, University of South Australia, Adelaide, SA, Australia

    Marianna Sigala

  2. Business School, University of Wolverhampton, Wolverhampton, UK

    Roya Rahimi

  3. School of Mathemetics and Computing, University of Wolverhampton, Wolverhampton, UK

    Mike Thelwall

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Thelwall, M. (2019). Sentiment Analysis for Tourism. In: Sigala, M., Rahimi, R., Thelwall, M. (eds) Big Data and Innovation in Tourism, Travel, and Hospitality. Springer, Singapore. https://doi.org/10.1007/978-981-13-6339-9_6

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