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Using social media user attributes to understand human–environment interactions at urban parks
Urban parks and green spaces are among the few places where city dwellers can have regular contact with nature and engage in outdoor recreation. Social media data provide opportunities to understand such human–environment interactions. While studies have demonstrated that geo-located photographs are...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6972848/ https://www.ncbi.nlm.nih.gov/pubmed/31965008 http://dx.doi.org/10.1038/s41598-020-57864-4 |
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author | Song, Xiao Ping Richards, Daniel R. Tan, Puay Yok |
author_facet | Song, Xiao Ping Richards, Daniel R. Tan, Puay Yok |
author_sort | Song, Xiao Ping |
collection | PubMed |
description | Urban parks and green spaces are among the few places where city dwellers can have regular contact with nature and engage in outdoor recreation. Social media data provide opportunities to understand such human–environment interactions. While studies have demonstrated that geo-located photographs are useful indicators of recreation across different spaces, recreation behaviour also varies between different groups of people. Our study used social media to assess behavioural patterns across different groups of park users in tropical Singapore. 4,674 users were grouped based on the location and content of their photographs on the Flickr platform. We analysed how these groups varied spatially in the parks they visited, as well as in their photography behaviour. Over 250,000 photographs were analysed, including those uploaded and favourited by users, and all photographs taken at city parks. There were significant differences in the number and types of park photographs between tourists and locals, and between user-group axes formed from users’ photograph content. Spatial mapping of different user groups showed distinct patterns in the parks they were attracted to. Future work should consider such variability both within and between data sources, to provide a more context-dependent understanding of human–environment interactions and preferences for outdoor recreation. |
format | Online Article Text |
id | pubmed-6972848 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-69728482020-01-27 Using social media user attributes to understand human–environment interactions at urban parks Song, Xiao Ping Richards, Daniel R. Tan, Puay Yok Sci Rep Article Urban parks and green spaces are among the few places where city dwellers can have regular contact with nature and engage in outdoor recreation. Social media data provide opportunities to understand such human–environment interactions. While studies have demonstrated that geo-located photographs are useful indicators of recreation across different spaces, recreation behaviour also varies between different groups of people. Our study used social media to assess behavioural patterns across different groups of park users in tropical Singapore. 4,674 users were grouped based on the location and content of their photographs on the Flickr platform. We analysed how these groups varied spatially in the parks they visited, as well as in their photography behaviour. Over 250,000 photographs were analysed, including those uploaded and favourited by users, and all photographs taken at city parks. There were significant differences in the number and types of park photographs between tourists and locals, and between user-group axes formed from users’ photograph content. Spatial mapping of different user groups showed distinct patterns in the parks they were attracted to. Future work should consider such variability both within and between data sources, to provide a more context-dependent understanding of human–environment interactions and preferences for outdoor recreation. Nature Publishing Group UK 2020-01-21 /pmc/articles/PMC6972848/ /pubmed/31965008 http://dx.doi.org/10.1038/s41598-020-57864-4 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Song, Xiao Ping Richards, Daniel R. Tan, Puay Yok Using social media user attributes to understand human–environment interactions at urban parks |
title | Using social media user attributes to understand human–environment interactions at urban parks |
title_full | Using social media user attributes to understand human–environment interactions at urban parks |
title_fullStr | Using social media user attributes to understand human–environment interactions at urban parks |
title_full_unstemmed | Using social media user attributes to understand human–environment interactions at urban parks |
title_short | Using social media user attributes to understand human–environment interactions at urban parks |
title_sort | using social media user attributes to understand human–environment interactions at urban parks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6972848/ https://www.ncbi.nlm.nih.gov/pubmed/31965008 http://dx.doi.org/10.1038/s41598-020-57864-4 |
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