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Tourism Attraction Selection with Sentiment Analysis of Online Reviews Based on Probabilistic Linguistic Term Sets and the IDOCRIW-COCOSO Model

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Abstract

The Internet has provided many platforms for tourists to spread tourism-related information, resulting in a large amount of online review data on tourist attractions. Mining and analyzing online reviews by using modern information technology are of great importance. They affect tourists’ travel decisions and ensure the effective management of tourism attraction managers. We establish a multi-dimensional comprehensive evaluation indicator system based on the online reviews of 5A-level tourism attractions in 31 provinces and cities of China. We also utilize probabilistic linguistic term sets (PLTSs) to process the result of sentiment orientation and establish the integrated determination of objective criteria weights (IDOCRIW)-combined compromise solution (COCOSO) model to calculate the aggregate weight of attributes and rank the final evaluation of tourism attractions. Finally, we apply the proposed model to a case study on selecting tourism attractions and illustrate the effectiveness of this work.

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Acknowledgements

This work was supported by the Humanities and Social Sciences Program of the Ministry of Education (Grant No. 20YJC630095), the National Natural Science Foundation of China (Grant Nos. 71501019, 71971151), Postdoctoral Research Foundation of China (Grant No. 2018M631069), Soft Science Research Program of Chengdu (Grant No. 2017-RK00-00425-ZF), General Project of Regional Public Management Informatization Research Center of Key Social Science Research Base in Sichuan (Grant No. QGXH20-03), the Funding Program for Middle aged Core Teachers at Chengdu University of Technology (Grant No. 2019KY3704203), Philosophy and Social Science Research Foundation of Chengdu University of Technology (Grant No. YJ2019-NS004), and the Special Funding for Post-doctoral Research Projects of Sichuan in 2017 Named “dynamic evolution of multi-system coupling in resource-oriented cities of western China from a technology innovation-driven perspective” and the Program of Graduate Education Reform Program at Chengdu University of Technology (Grant No.10800-00009824), Key Project of National Park Research Center of Sichuan Social Science Research Base (Grant No. GJGY2020-ZD001) “Research on the path to improve tourism ecological value of Giant Panda National Park from the perspective of host-guest governance.”

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Correspondence to Yong Qin.

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Luo, Y., Zhang, X., Qin, Y. et al. Tourism Attraction Selection with Sentiment Analysis of Online Reviews Based on Probabilistic Linguistic Term Sets and the IDOCRIW-COCOSO Model. Int. J. Fuzzy Syst. 23, 295–308 (2021). https://doi.org/10.1007/s40815-020-00969-9

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  • DOI: https://doi.org/10.1007/s40815-020-00969-9

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