ABSTRACT
This study investigated what (risk) information related to COVID-19 was most amplified through online discussions in environment-focused communities and how amplification and ripple effects evolved over time. The population of posts and comments (N = 14,156 observations) posted to 135 environment-focused subreddits from Dec. 1, 2019-Aug. 31, 2020 containing key terms related to COVID-19 was downloaded and subjected to computational content analysis via Leximancer to observe conceptual phenomena that emerged in the data and extract themes based on word-like associations. To examine how online discussion evolved over time, stepwise segmented regression was employed to identify revolutionary breakpoints – significant changes in the volume of conversation over time. Analysis revealed five time periods in the dataset, and concept maps were generated to understand prominent themes in each. Omnibus results revealed themes highlighting positive and negative environmental consequences associated with COVID-19. Analysis revealed a more nuanced trajectory of how the frequency and content of conversations evolved over time.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes
1 Excluded subreddits included the following: Biochemistry, Earthquakes, genetics, geospatial, gis, Microbiology, Nuclear Power, Science, Statistics, StormComing, Tropical Weather, urbanplanning, and weather.