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Destination image through social media analytics and survey method

Michael S. Lin (School of Hotel and Tourism Management, The Hong Kong Polytechnic University, Kowloon, China)
Yun Liang (Department of Recreation, Park, and Tourism Management, The Pennsylvania State University, University Park, Pennsylvania, USA)
Joanne X. Xue (School of Hospitality Management, The Pennsylvania State University, University Park, Pennsylvania, USA)
Bing Pan (Department of Recreation, Park, and Tourism Management, The Pennsylvania State University, University Park, Pennsylvania, USA)
Ashley Schroeder (Department of Recreation, Park, and Tourism Management, The Pennsylvania State University, University Park, Pennsylvania, USA)

International Journal of Contemporary Hospitality Management

ISSN: 0959-6119

Article publication date: 10 June 2021

Issue publication date: 9 August 2021

1913

Abstract

Purpose

Recent tourism research has adopted social media analytics (SMA) to examine tourism destination image (TDI) and gain timely insights for marketing purposes. Comparing the methodologies of SMA and intercept surveys would provide a more in-depth understanding of both methodologies and a more holistic understanding of TDI than each method on their own. This study aims to investigate the unique merits and biases of SMA and a traditional visitor intercept survey.

Design/methodology/approach

This study collected and compared data for the same tourism destination from two sources: responses from a visitor intercept survey (n = 1,336) and Flickr social media photos and metadata (n = 11,775). Content analysis, machine learning and text analysis techniques were used to analyze and compare the destination image represented from both methods.

Findings

The results indicated that the survey data and social media data shared major similarities in the identified key image phrases. Social media data revealed more diverse and more specific aspects of the destination, whereas survey data provided more insights in specific local landmarks. Survey data also included additional subjective judgment and attachment towards the destination. Together, the data suggested that social media data should serve as an additional and complementary source of information to traditional survey data.

Originality/value

This study fills a research gap by comparing two methodologies in obtaining TDI: SMA and a traditional visitor intercept survey. Furthermore, within SMA, photo and metadata are compared to offer additional awareness of social media data’s underlying complexity. The results showed the limitations of text-based image questions in surveys. The findings provide meaningful insights for tourism marketers by having a more holistic understanding of TDI through multiple data sources.

Keywords

Acknowledgements

The authors would like to thank Happy Valley Adventure Bureau for supporting the visitor intercept survey project with OSP No. 208653.

Citation

Lin, M.S., Liang, Y., Xue, J.X., Pan, B. and Schroeder, A. (2021), "Destination image through social media analytics and survey method", International Journal of Contemporary Hospitality Management, Vol. 33 No. 6, pp. 2219-2238. https://doi.org/10.1108/IJCHM-08-2020-0861

Publisher

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Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

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