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A Graph Theory approach to assess nature’s contribution to people at a global scale
The use of Graph Theory on social media data is a promising approach to identify emergent properties of the complex physical and cognitive interactions that occur between humans and nature. To test the effectivity of this approach at global scales, Instagram posts from fourteen natural areas were se...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8079382/ https://www.ncbi.nlm.nih.gov/pubmed/33907282 http://dx.doi.org/10.1038/s41598-021-88745-z |
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author | de Juan, Silvia Ospina-Álvarez, Andrés Villasante, Sebastián Ruiz-Frau, Ana |
author_facet | de Juan, Silvia Ospina-Álvarez, Andrés Villasante, Sebastián Ruiz-Frau, Ana |
author_sort | de Juan, Silvia |
collection | PubMed |
description | The use of Graph Theory on social media data is a promising approach to identify emergent properties of the complex physical and cognitive interactions that occur between humans and nature. To test the effectivity of this approach at global scales, Instagram posts from fourteen natural areas were selected to analyse the emergent discourse around these areas. The fourteen areas, known to provide key recreational, educational and heritage values, were investigated with different centrality metrics to test the ability of Graph Theory to identify variability in ecosystem social perceptions and use. Instagram data (i.e., hashtags associated to photos) was analysed with network centrality measures to characterise properties of the connections between words posted by social media users. With this approach, the emergent properties of networks of hashtags were explored to characterise visitors’ preferences (e.g., cultural heritage or nature appreciation), activities (e.g., diving or hiking), preferred habitats and species (e.g., forest, beach, penguins), and feelings (e.g., happiness or place identity). Network analysis on Instagram hashtags allowed delineating the users’ discourse around a natural area, which provides crucial information for effective management of popular natural spaces for people. |
format | Online Article Text |
id | pubmed-8079382 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-80793822021-04-28 A Graph Theory approach to assess nature’s contribution to people at a global scale de Juan, Silvia Ospina-Álvarez, Andrés Villasante, Sebastián Ruiz-Frau, Ana Sci Rep Article The use of Graph Theory on social media data is a promising approach to identify emergent properties of the complex physical and cognitive interactions that occur between humans and nature. To test the effectivity of this approach at global scales, Instagram posts from fourteen natural areas were selected to analyse the emergent discourse around these areas. The fourteen areas, known to provide key recreational, educational and heritage values, were investigated with different centrality metrics to test the ability of Graph Theory to identify variability in ecosystem social perceptions and use. Instagram data (i.e., hashtags associated to photos) was analysed with network centrality measures to characterise properties of the connections between words posted by social media users. With this approach, the emergent properties of networks of hashtags were explored to characterise visitors’ preferences (e.g., cultural heritage or nature appreciation), activities (e.g., diving or hiking), preferred habitats and species (e.g., forest, beach, penguins), and feelings (e.g., happiness or place identity). Network analysis on Instagram hashtags allowed delineating the users’ discourse around a natural area, which provides crucial information for effective management of popular natural spaces for people. Nature Publishing Group UK 2021-04-27 /pmc/articles/PMC8079382/ /pubmed/33907282 http://dx.doi.org/10.1038/s41598-021-88745-z Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article de Juan, Silvia Ospina-Álvarez, Andrés Villasante, Sebastián Ruiz-Frau, Ana A Graph Theory approach to assess nature’s contribution to people at a global scale |
title | A Graph Theory approach to assess nature’s contribution to people at a global scale |
title_full | A Graph Theory approach to assess nature’s contribution to people at a global scale |
title_fullStr | A Graph Theory approach to assess nature’s contribution to people at a global scale |
title_full_unstemmed | A Graph Theory approach to assess nature’s contribution to people at a global scale |
title_short | A Graph Theory approach to assess nature’s contribution to people at a global scale |
title_sort | graph theory approach to assess nature’s contribution to people at a global scale |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8079382/ https://www.ncbi.nlm.nih.gov/pubmed/33907282 http://dx.doi.org/10.1038/s41598-021-88745-z |
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