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Perceptions of Cultural Ecosystem Services in Urban Parks Based on Social Network Data

Author

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  • Peichao Dai

    (School of Environment Science and Spatial Informatics, China University of Mining and Technology, 1st Daxue Road, Xuzhou 221000, China)

  • Shaoliang Zhang

    (School of Environment Science and Spatial Informatics, China University of Mining and Technology, 1st Daxue Road, Xuzhou 221000, China)

  • Zanxu Chen

    (School of Environment Science and Spatial Informatics, China University of Mining and Technology, 1st Daxue Road, Xuzhou 221000, China)

  • Yunlong Gong

    (School of Environment Science and Spatial Informatics, China University of Mining and Technology, 1st Daxue Road, Xuzhou 221000, China)

  • Huping Hou

    (School of Environment Science and Spatial Informatics, China University of Mining and Technology, 1st Daxue Road, Xuzhou 221000, China)

Abstract

The value of a cultural ecosystem service depends on the perception of different cultural service categories. However, the data sources used in research on the perception of cultural service have limitations that mainly depend on social investigation, leading to slow progress in cultural service evaluation. With the advent of the era of network big data, social media provides a new data source for the study of cultural ecosystem service perception, so that the study of these services is expected to make new breakthroughs. Using search crawler software, this paper reviewed 7257 online comments related to 19 city parks in Xuzhou City, China. With the help of Rost Content mining semantic analysis software, the comment sentences were divided into keywords, and the Delphi expert method was used to classify these keywords. Thus, a cultural service perception database was established. Through statistical analysis, with the help of ArcGIS software, various cultural services were analyzed. The results showed that (1) the cultural services of urban parks could be divided into seven types (i.e., aesthetics, recreation, sports, inspiration, education, cultural heritage, and spiritual satisfaction) using social network comment data. (2) High-frequency keywords of online comment data can serve as the core basis during an analysis of the perception of cultural services by visitors of city parks. However, a large gap exists in the number of high frequency keywords in different parks. For example, Yunlong Lake Park has 2887 keywords, while Kuaizai Ting Park has only 33. (3) Differences exist in the perception of cultural service in urban parks, the park’s scale, and characteristics determine the visitor’s cultural service perception level. The aesthetic and recreation types were the most easily perceived, and 68% and 63% parks have the above two perceptual records, respectively. Therefore, the social media comment data has the ability to document perception of each park’s cultural service type and its differences, which can serve as the cultural ecosystem service perception as well as the valuation data source, to supplement the social investigation.

Suggested Citation

  • Peichao Dai & Shaoliang Zhang & Zanxu Chen & Yunlong Gong & Huping Hou, 2019. "Perceptions of Cultural Ecosystem Services in Urban Parks Based on Social Network Data," Sustainability, MDPI, vol. 11(19), pages 1-14, September.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:19:p:5386-:d:271911
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    2. Dai, Peichao & Zhang, Shaoliang & Gong, Yunlong & Zhou, Yuan & Hou, Huping, 2022. "A crowd-sourced valuation of recreational ecosystem services using mobile signal data applied to a restored wetland in China," Ecological Economics, Elsevier, vol. 192(C).
    3. Shrestha, Kripa & Shakya, Bandana & Adhikari, Biraj & Nepal, Mani & Shaoliang, Yi, 2023. "Ecosystem services valuation for conservation and development decisions: A review of valuation studies and tools in the Far Eastern Himalaya," Ecosystem Services, Elsevier, vol. 61(C).
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    5. Fox, Nathan & Graham, Laura J. & Eigenbrod, Felix & Bullock, James M. & Parks, Katherine E., 2021. "Reddit: A novel data source for cultural ecosystem service studies," Ecosystem Services, Elsevier, vol. 50(C).
    6. Yunseon Choe & Jiyoon Lee & Gyehee Lee, 2022. "Exploring Values via the Innovative Application of Social Media with Parks Amid COVID-19: A Qualitative Content Analysis of Text and Images Using ATLAS.ti," Sustainability, MDPI, vol. 14(20), pages 1-16, October.
    7. Stefano Bruzzese & Wasim Ahmed & Simone Blanc & Filippo Brun, 2022. "Ecosystem Services: A Social and Semantic Network Analysis of Public Opinion on Twitter," IJERPH, MDPI, vol. 19(22), pages 1-15, November.
    8. Gabriele Zabelskyte & Nadja Kabisch & Zaneta Stasiskiene, 2022. "Patterns of Urban Green Space Use Applying Social Media Data: A Systematic Literature Review," Land, MDPI, vol. 11(2), pages 1-21, February.
    9. Fiona Nevzati & Mart Külvik & Joanna Storie & Liisa-Maria Tiidu & Simon Bell, 2023. "Assessment of Cultural Ecosystem Services and Well-Being: Testing a Method for Evaluating Natural Environment and Contact Types in the Harku Municipality, Estonia," Sustainability, MDPI, vol. 15(13), pages 1-24, June.
    10. 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.
    11. Diana Andreea Onose & Ioan Cristian Iojă & Mihai Răzvan Niță & Gabriel Ovidiu Vânău & Ana Maria Popa, 2020. "Too Old for Recreation? How Friendly Are Urban Parks for Elderly People?," Sustainability, MDPI, vol. 12(3), pages 1-14, January.
    12. Hongxu Guo & Zhuoqiao Luo & Mengtian Li & Shumin Kong & Haiyan Jiang, 2022. "A Literature Review of Big Data-Based Urban Park Research in Visitor Dimension," Land, MDPI, vol. 11(6), pages 1-17, June.
    13. Gugulica, Madalina & Burghardt, Dirk, 2023. "Mapping indicators of cultural ecosystem services use in urban green spaces based on text classification of geosocial media data," Ecosystem Services, Elsevier, vol. 60(C).

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