Assessing Brazilian protected areas through social media: Insights from 10 years of public interest and engagement

PLoS One. 2023 Oct 30;18(10):e0293581. doi: 10.1371/journal.pone.0293581. eCollection 2023.

Abstract

Social media platforms are a valuable source of data for investigating cultural and political trends related to public interest in nature and conservation. Here, we use the micro-blogging social network Twitter to explore trends in public interest in Brazilian protected areas (PAs). We identified ~400,000 Portuguese language tweets pertaining to all categories of Brazilian PAs over a ten-year period (1 January 2011-31 December 2020). We analysed the content of these tweets and calculated metrics of user engagement (likes and retweets) to uncover patterns and drivers of public interest in Brazilian PAs. Our results indicate that users / tweets mentioning PAs remained stable throughout the sample period. However, engagement with tweets grew steeply, particularly from 2018 onward and coinciding with a change in the Brazilian federal government. Furthermore, public interest was not evenly distributed across PAs; while national parks were the subject of the most tweets, mainly related to tourism activities, tweets related to conflicts among park users and managers were more likely to engage Twitter users. Our study highlights that automatic or semi-automatic monitoring of social media content and engagement has great potential as an early warning system to identify emerging conflicts and to generate data and metrics to support PA policy, governance and management.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Blogging
  • Brazil
  • Humans
  • Language
  • Social Media*

Grants and funding

This work was supported by Fundo Brasileiro para a Biodiversidade (FUNBIO) and Instituto Humanize (#026/2021). RJL, ACMM and ARC are funded by Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) (#309879/2019-1; #309980/2018-6; #313334/2018-8). RJL and ACMM are supported via the European Union’s Horizon 2020 research and innovation programme under grant agreement No 854248. CNS is currently supported by CNPq doctoral grant (#141872/2020-9). RAC acknowledges funding from the Academy of Finland (Grant agreement #348352) and the KONE Foundation (Grant agreement #202101976).