A1 Refereed original research article in a scientific journal
Using social media and machine learning to understand sentiments towards Brazilian National Parks
Authors: Souza Carolina Neves, Martínez-Arribas Javier, Correia Ricardo A., Almeida João A.G.R., Ladle Richard, Vaz Ana Sofia, Malhado Ana Cláudia
Publisher: Elsevier
Publication year: 2024
Journal: Biological Conservation
Journal name in source: Biological Conservation
Article number: 110557
Volume: 293
ISSN: 0006-3207
eISSN: 1873-2917
DOI: https://doi.org/10.1016/j.biocon.2024.110557
Web address : https://doi.org/10.1016/j.biocon.2024.110557
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/387564318
Abstract
Protected areas (PAs) play a vital role in the conservation of natural and cultural heritage while supporting local livelihoods. However, in Brazil, where limited resources and poor effectiveness lead to negative sentiments and are leveraged as criticism towards PAs, it is necessary to better comprehend public perceptions of Brazilian PAs and identify the key factors contributing to negative sentiments. Here, we use data from online discussions about Brazilian national parks (NPs) on Twitter and sentiment analysis to explore this question. We classified the sentiment of ∼100,000 tweets collected over a twelve-year period (2011−2022) using the BERTimbau Base model. We also performed a topic modelling with the BERTopic model to identify prevalent subjects concerning Brazilian NPs. We identified 18,388 (17.30 %) posts expressing negative sentiment towards NPs, mostly associated with wildfires occurring between 2011 and 2017 and concerning government decisions impacting conservation efforts after 2019. The results revealed six prominent topics: (1) Wildfires; (2) Security; (3) Regulations; (4) Wildlife roadkill; (5) Privatization; (6) Lack of financial resources, reflecting a diverse range of negative sentiments regarding the parks, surpassing isolated events. Furthermore, examining specific topics on a per-park basis proved beneficial in identifying distinct issues and conflicts in the five most tweeted NPs, facilitating targeted conservation actions. Using social media data to better understand public perceptions of NPs can strengthen their management and governance by reinforcing their conservation initiatives and enhancing visitor experiences. Our findings underscore the value of sentiment analysis in identifying gaps and driving improvements in the management of protected areas.
Protected areas (PAs) play a vital role in the conservation of natural and cultural heritage while supporting local livelihoods. However, in Brazil, where limited resources and poor effectiveness lead to negative sentiments and are leveraged as criticism towards PAs, it is necessary to better comprehend public perceptions of Brazilian PAs and identify the key factors contributing to negative sentiments. Here, we use data from online discussions about Brazilian national parks (NPs) on Twitter and sentiment analysis to explore this question. We classified the sentiment of ∼100,000 tweets collected over a twelve-year period (2011−2022) using the BERTimbau Base model. We also performed a topic modelling with the BERTopic model to identify prevalent subjects concerning Brazilian NPs. We identified 18,388 (17.30 %) posts expressing negative sentiment towards NPs, mostly associated with wildfires occurring between 2011 and 2017 and concerning government decisions impacting conservation efforts after 2019. The results revealed six prominent topics: (1) Wildfires; (2) Security; (3) Regulations; (4) Wildlife roadkill; (5) Privatization; (6) Lack of financial resources, reflecting a diverse range of negative sentiments regarding the parks, surpassing isolated events. Furthermore, examining specific topics on a per-park basis proved beneficial in identifying distinct issues and conflicts in the five most tweeted NPs, facilitating targeted conservation actions. Using social media data to better understand public perceptions of NPs can strengthen their management and governance by reinforcing their conservation initiatives and enhancing visitor experiences. Our findings underscore the value of sentiment analysis in identifying gaps and driving improvements in the management of protected areas.
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