Profiling Cultural Tourists by Using User Generated Big Data from Online Travel Agencies
Authors: 
Xiaogang Zhao, Siwei Dong, Yiwei Dang, Hai Shen, Jun Hou, Ge LiAuthors Info & Claims
Xiaogang Zhao, Siwei Dong, Yiwei Dang, Hai Shen, Jun Hou, Ge LiAuthors Info & ClaimsPages 10 - 14
Abstract
Cultural tourism, as one of the most popular forms of tourism, has recently witnessed a remarkable development. However, rapid development of cultural tourism has brought fierce competition. In order to increase the attractiveness of scenic spots, it is very necessary for tourism enterprises to accurately understand cultural tourists‘ preference. This paper proposes a systematic method for profiling cultural tourists based on user generated big data. In this method, topic model, sentiment analysis and clustering algorithms are combined to cluster tourists, and then multinomial logistic regression model are applied to match tourists’ basic attributes. Calculation results show that cultural tourists are mainly divided into four groups with different characteristics. According to the characteristics of each group, suggestions for improving the management of scenic spots are put forward.
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- Profiling Cultural Tourists by Using User Generated Big Data from Online Travel Agencies
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Published In
January 2023
101 pages
ISBN:9781450398022
DOI:10.1145/3589845
Copyright © 2023 ACM.
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 22 June 2023
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ICCDE 2023
ICCDE 2023: 2023 9th International Conference on Computing and Data Engineering
January 6 - 8, 2023
Haikou, China
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