RESUMO
Social media data is a rich source of information to assess human activities in catastrophic events. Here, we use social media data to understand how the 2019 Brazilian oil spill influenced social attitudes. Data were collected from the globally popular Instagram platform between August 1, 2019 and March 1, 2020. First, we manually identified the 5 most popular (portuguese language) hashtags related to the oil spill #oleonononordeste; #desastreambiental; #marsemoleo; #sosnordeste; #marsempetroleo. In the sequence, we collected information on captions, post metadata and users associated with posts retrieved using the selected hashtags. We identified a total of 7,413 posts. These posts were grouped in topics: government (47.76%), protest (24.37%), volunteers (24.45%), biodiversity (0.003%), origin (0.006%), tourism (0.008%) and others (0.016%). All topics had the peak of posts in October and November 2019. Nevertheless, interest in the oil spill was temporary, with most posts appearing in the 2-4 months after the beginning of the disaster. Our findings illustrate the enormous potential of using social media data for understanding and monitoring human engagement with environmental disasters, but also suggest that conservationists and environmental groups may only have a limited 'window of opportunity' to engage and mobilize public support for remediation and restoration efforts.
Assuntos
Poluição por Petróleo , Mídias Sociais , Brasil , Humanos , Poluição por Petróleo/efeitos adversosRESUMO
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.