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Analysis of Tourism Experience in Haizhu National Wetland Park Based on Web Text

Author

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  • Pei Lin

    (College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou 510642, China)

  • Lili Chen

    (College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou 510642, China)

  • Zeshun Luo

    (College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou 510642, China)

Abstract

Most studies on wetland parks focus on resource surveys and evaluations, park planning and design, and the construction of hardware facilities. Only a few studies have covered tourism experiences. With the rapid development of online media, online text data have become a prominent research direction for tourism experiences. Based on the web text analysis method and importance-performance analysis, Rost Content Mining 6 software was used. This served to analyze word frequency, semantic web analysis, and sentiment analysis, and to explain the web text about Haizhu National Wetland Park. It also helped to find problems experienced by tourists and their underlying reasons and proposed improvement strategies. The results showed that the overall quality of the tourism experience in Haizhu National Wetland Park was relatively high. However, some of the negative comments mainly focused on the lack of humanistic landscape construction, lagging infrastructure, and poor management services. By combining research results, improvement strategies were proposed that addressed infrastructure, management services, scenic spot publicity, ecological environmental protection, and so on. These could help to enhance tourism experiences.

Suggested Citation

  • Pei Lin & Lili Chen & Zeshun Luo, 2022. "Analysis of Tourism Experience in Haizhu National Wetland Park Based on Web Text," Sustainability, MDPI, vol. 14(5), pages 1-16, March.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:5:p:3011-:d:764175
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    References listed on IDEAS

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    Cited by:

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    3. Siya Cheng & Ziling Huang & Haochen Pan & Shuaiqing Wang & Xiaoyu Ge, 2022. "Comparative Study of Park Evaluation Based on Text Analysis of Social Media: A Case Study of 50 Popular Parks in Beijing," Sustainability, MDPI, vol. 14(19), pages 1-34, October.
    4. Dongfang Ma & Shaojie Zhang & Tieqiao Xiao & Taotao Shui, 2023. "Aspects of New and Old Urban Parks Most Valued by Residents on Social Media: A Case Study in Hefei," Sustainability, MDPI, vol. 15(18), pages 1-21, September.
    5. Xiaopiao Yang & Yuluan Zhao & Jia Zhao & Chao Shi & Bailu Deng, 2022. "Tourists’ Perceived Attitudes toward the Famous Terraced Agricultural Cultural Heritage Landscape in China," Agriculture, MDPI, vol. 12(9), pages 1-13, September.
    6. Vladimir Stojanović & Maja Mijatov Ladičorbić & Aleksandra S. Dragin & Marija Cimbaljević & Sanja Obradović & Dragan Dolinaj & Tamara Jovanović & Anđelija Ivkov-Džigurski & Jelena Dunjić & Milena Nede, 2023. "Tourists’ Motivation in Wetland Destinations: Gornje Podunavlje Special Nature Reserve Case Study (Mura-Drava-Danube Transboundary Biosphere Reserve)," Sustainability, MDPI, vol. 15(12), pages 1-21, June.
    7. Shuhao Liu & Chang Su & Ruochen Yang & Jianye Zhao & Kun Liu & Kwangmin Ham & Shiro Takeda & Junhua Zhang, 2022. "Using Crowdsourced Big Data to Unravel Urban Green Space Utilization during COVID-19 in Guangzhou, China," Land, MDPI, vol. 11(7), pages 1-20, June.
    8. Yanlong Guo & Jiaying Yu & Han Zhang & Zuoqing Jiang, 2022. "A Study on Cultural Context Perception in Huizhou Cultural and Ecological Reserve Based on Multi-Criteria Decision Analysis," Sustainability, MDPI, vol. 14(24), pages 1-20, December.

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