Validating social media data reliability for cultural ecosystem services mapping in data-scarce GIAHS: A mixed-methods approach in hani rice Terraces

• We assessed the reliability of social media data in mapping cultural services where data was sparse. • Social media data method was reliable and identified more places with cultural services value. • Aesthetic value > scientific & educational value and cultural heritage value > cultural diversity value in Hani terraces. • Questionnaire method revealed higher cultural services values than social media data method. Cultural ecosystem services (CESs) are subjective and intangible, making their assessment challenging. While the application of social media data in assessing and mapping the cultural services of the ecosystem has made rapid progress, this approach relies on active social media users and large sample size of social media data. The reliability of social media data-based method in less developed areas, where such conditions may not be met, remains largely unverified. This study focuses on the Yuanyang Hani Terraces, a Globally Important Agricultural Heritage site located in the remote mountains of southwest China. We compared the value and distribution of CESs as revealed by social media data and questionnaire data, and estimated the applicability of social media data in regions with limited data availability. The results show that: (1) Among the places identified as possessing CESs via questionnaire method, 90 % of places with aesthetic value (AV), 90 % of places with cultural heritage value (CHV), 91 % places with cultural diversity value (CDV), and 80 % of places with scientific & educational value (SEV) were also identified using social media data. The intraclass correlation efficient value for the two-method reached 0.96,0.84,0.79, and 0.76, respectively, indicating a high consistency level. Furthermore, social media data-based method identified more CES places than the traditional method. (2) the CESs in the core area of Hani Terraces showed a pattern of AV > SEV and CHV > CDV. Places with AV mainly located in Duoyishu-Aichun area, Bada-Laoyingzui area and Laohuzui aera. Places with CHV included Shengcun (a local town), museum, famous folk villages, and county houses cluster. Places with SEV were mainly two traditional villages, the museum, and the tourist center where documentary and exhibitions of the Hani Terraces were provided. This study showed that social media data provides highly consistent results with traditional questionnaire method for assessing and mapping CES and presents a cost-effective alternative for similar studies in less developed areas where social media data is sparse.

Authors

Institutions

Publication Details

Journal
Ecological Indicators
Published
2025-05-01
DOI
https://doi.org/10.1016/j.ecolind.2025.113530
Citations
5
Primary Topic
Land Use and Ecosystem Services
Type
article
Field-Weighted Citation Impact
5.53
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Validating social media data reliability for cultural ecosystem services mapping in data-scarce GIAHS: A mixed-methods approach in hani rice Terraces

Liu Yang, Xiaoyan Wei, Yanbo Li
5 citations
Ecological Indicators
Land Use and Ecosystem Services
5.53
article

Validating social media data reliability for cultural ecosystem services mapping in data-scarce GIAHS: A mixed-methods approach in hani rice Terraces

Liu Yang, Xiaoyan Wei, Yanbo Li
article en
5 citations

Abstract

• We assessed the reliability of social media data in mapping cultural services where data was sparse. • Social media data method was reliable and identified more places with cultural services value. • Aesthetic value > scientific & educational value and cultural heritage value > cultural diversity value in Hani terraces. • Questionnaire method revealed higher cultural services values than social media data method. Cultural ecosystem services (CESs) are subjective and intangible, making their assessment challenging. While the application of social media data in assessing and mapping the cultural services of the ecosystem has made rapid progress, this approach relies on active social media users and large sample size of social media data. The reliability of social media data-based method in less developed areas, where such conditions may not be met, remains largely unverified. This study focuses on the Yuanyang Hani Terraces, a Globally Important Agricultural Heritage site located in the remote mountains of southwest China. We compared the value and distribution of CESs as revealed by social media data and questionnaire data, and estimated the applicability of social media data in regions with limited data availability. The results show that: (1) Among the places identified as possessing CESs via questionnaire method, 90 % of places with aesthetic value (AV), 90 % of places with cultural heritage value (CHV), 91 % places with cultural diversity value (CDV), and 80 % of places with scientific & educational value (SEV) were also identified using social media data. The intraclass correlation efficient value for the two-method reached 0.96,0.84,0.79, and 0.76, respectively, indicating a high consistency level. Furthermore, social media data-based method identified more CES places than the traditional method. (2) the CESs in the core area of Hani Terraces showed a pattern of AV > SEV and CHV > CDV. Places with AV mainly located in Duoyishu-Aichun area, Bada-Laoyingzui area and Laohuzui aera. Places with CHV included Shengcun (a local town), museum, famous folk villages, and county houses cluster. Places with SEV were mainly two traditional villages, the museum, and the tourist center where documentary and exhibitions of the Hani Terraces were provided. This study showed that social media data provides highly consistent results with traditional questionnaire method for assessing and mapping CES and presents a cost-effective alternative for similar studies in less developed areas where social media data is sparse.

Ecological IndicatorsVol. 175
Yunnan University (CN), Yunnan Provincial Department of Education (CN)
Openalex Percentile: Top 4%
Land Use and Ecosystem Services
5.53
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.