tetano
Editor, Senior Moderator
Sci Total Environ
. 2021 Jan 7;768:144530.
doi: 10.1016/j.scitotenv.2020.144530. Online ahead of print.
Changes in human-nature relations during pandemic outbreaks: a big data analysis
Wanggi Jaung[SUP] 1 [/SUP]
Affiliations
Abstract
Pandemic outbreaks can cause diverse impacts on society by altering human-nature relations. This study analyzed these relational changes during the severe acute respiratory syndrome (SARS), Swine flu, Middle East respiratory syndrome (MERS), and Ebola outbreaks by applying machine learning and big data analyses of global news articles. The results showed that social-ecological systems play vital roles in analyzing indirect pandemic impacts. Herein, major pandemic impacts, including reduced use of cultural ecosystem services, can be analyzed by big data analyses at the global scale. All the identified pandemic impacts herein were linked to provisioning and cultural ecosystem services, implying that these ecosystem services might be more recognized or valued more by the public than regulating and supporting ecosystem services. Further, the pandemic impacts were presented with human-centric views, indicating a challenge to adapting nature-based solutions to mitigate the risk of future pandemic emergences. These findings will advance the current knowledge of diverse pandemic impacts and human-nature relations.
Keywords: Coronaviruses; Ecosystem services; Media analysis; Natural language processing; Social-ecological systems.
. 2021 Jan 7;768:144530.
doi: 10.1016/j.scitotenv.2020.144530. Online ahead of print.
Changes in human-nature relations during pandemic outbreaks: a big data analysis
Wanggi Jaung[SUP] 1 [/SUP]
Affiliations
- PMID: 33453532
- DOI: 10.1016/j.scitotenv.2020.144530
Abstract
Pandemic outbreaks can cause diverse impacts on society by altering human-nature relations. This study analyzed these relational changes during the severe acute respiratory syndrome (SARS), Swine flu, Middle East respiratory syndrome (MERS), and Ebola outbreaks by applying machine learning and big data analyses of global news articles. The results showed that social-ecological systems play vital roles in analyzing indirect pandemic impacts. Herein, major pandemic impacts, including reduced use of cultural ecosystem services, can be analyzed by big data analyses at the global scale. All the identified pandemic impacts herein were linked to provisioning and cultural ecosystem services, implying that these ecosystem services might be more recognized or valued more by the public than regulating and supporting ecosystem services. Further, the pandemic impacts were presented with human-centric views, indicating a challenge to adapting nature-based solutions to mitigate the risk of future pandemic emergences. These findings will advance the current knowledge of diverse pandemic impacts and human-nature relations.
Keywords: Coronaviruses; Ecosystem services; Media analysis; Natural language processing; Social-ecological systems.