Evidence map›Paper›PMID 36915375›Full record

ArticleEnvironmental development2023

Twitterati on COVID-19 pandemic-environment linkage: Insights from mining one year of tweets.

Krishna Malakar, Partha Majumder, Chunhui Lu

Abstract read
In one paragraph

Article in Environmental development, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Krishna MalakarState Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing, China.
Partha MajumderState Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing, China.
Chunhui LuState Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic seems to have had positive (although short-lived, e.g., reduction in pollution due to lockdown) as well as negative (e.g., increasing plastic pollution due to use of disposable masks, etc.) impacts on the environment. The pandemic-environment linkage also includes circumstances when regions experienced extreme weather events, such as floods and cyclones, and disaster management became challenging. This study aims to examine the trends in public discourses on Twitter on these interactions between the pandemic and environment. The present study follows the most recent literature on understanding public perceptions - which acknowledges Twitter to be an abundant source of information on public discussions on any global issue, including the pandemic. A Python-based code is developed to extract Twitter data spanning over a year, and analyze the presence of covid-environment related keywords and other attributes. It is found that the Twitterati aggressively viewed the impacts (such as economic slowdown and high mortality) of the pandemic as miniatures of the results of future climate change. The community was also highly concerned about the varying air and plastic pollution levels with the change in lockdown and covid prevention policies. Extreme weather events were a high-frequency topic when they impacted countries such as India, the USA, Australia, the Philippines and Vietnam. This study makes a novel attempt to provide an overview of public discourses on the pandemic-environment linkage and; can be a crucial addition to the literature on assessing public perception of environmental threats through Twitter data mining.

Indexed as

Big data analyticsClimate changecomputational social scienceEnvironmental changeHuman-environment systemPollutionTwarc

Identifiers

PMID36915375
PMCPMC9970929

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.