Park, Sohyun;
Kim, Seungman;
Lee, Jaehoon;
Heo, Biyoung
Evolving norms: social media data analysis on parks and greenspaces perception changes before and after the COVID 19 pandemic using a machine learning approach
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Medientyp:
E-Artikel
Titel:
Evolving norms: social media data analysis on parks and greenspaces perception changes before and after the COVID 19 pandemic using a machine learning approach
Beteiligte:
Park, Sohyun;
Kim, Seungman;
Lee, Jaehoon;
Heo, Biyoung
Erschienen:
Springer Science and Business Media LLC, 2022
Erschienen in:
Scientific Reports, 12 (2022) 1
Sprache:
Englisch
DOI:
10.1038/s41598-022-17077-3
ISSN:
2045-2322
Entstehung:
Anmerkungen:
Beschreibung:
AbstractThis study provides a novel approach to understand human perception changes in their experiences of and interactions with public greenspaces during the early months of COVID-19. Using social media data and machine learning techniques, the study delivers new understandings of how people began to feel differently about their experiences compared to pre-COVID times. The study illuminates a renewed appreciation of nature as well as an emerging but prominent pattern of emotional and spiritual experiences expressed through a social media platform. Given that most park and recreational studies have almost exclusively examined whether park use increased or decreased during the pandemic, this research provides meaningful implications beyond the simple extensional visit pattern and lends weight to the growing evidences on changing perceptions over and the positive psychological impacts of nature. The study highlights the preeminent roles parks and greenspaces play during the pandemic and guides a new direction in future park development to support more natural elements and nature-oriented experiences from which emotional and spiritual well-being outcomes can be drawn.