Abstract
Geolocated social media data counts are increasingly used as proxy for number of visits in natural areas, including their spatial and temporal distribution. This paper synthesizes the empirical evidence concerning the correlation of social media data counts and visits through multi-level meta-analytical models. Analysis of 355 correlations from 41 studies reveals a strong correlation for annual number of visits over multiple sites (pooled Pearson's r = 0.73) and for monthly visits in a single site (pooled Pearson's r = 0.84). Using data from multiple social media sources improves the correlation. Mixed results are obtained with regard to the effect of social media penetration rate and designation as national park on the correlation. Future studies should focus on broadening the scope of investigation to middle and low-income countries, developing a systematic approach toward the use of covariates, and comparing the results from social media data to those from other emerging monitoring techniques.
| Original language | American English |
|---|---|
| Article number | 115325 |
| Journal | Journal of Environmental Management |
| Volume | 317 |
| DOIs | |
| State | Published - 1 Sep 2022 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 8 Decent Work and Economic Growth
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SDG 12 Responsible Consumption and Production
Keywords
- Cultural ecosystem services
- Meta-regression
- Nature-based tourism
- Passive crowdsourcing
- User-generated content
- Visitor monitoring
All Science Journal Classification (ASJC) codes
- Environmental Engineering
- Waste Management and Disposal
- Management, Monitoring, Policy and Law
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