Whether the Weather Will Help Us Weather the COVID-19 Pandemic: Using Machine Learning to Measure Twitter Users’ Perceptions

36 Pages Posted: 5 Aug 2020

See all articles by Marichi Gupta

Marichi Gupta

Harvard University - Harvard Medical School

Aditya Bansal

Indian Institute of Technology (IIT), Delhi

Bhav Jain

Massachusetts Institute of Technology (MIT)

Jillian Rochelle

Harvard University - Harvard Medical School

Atharv Oak

Massachusetts Institute of Technology (MIT)

Mohammad S. Jalali

Harvard University - Harvard Medical School

Date Written: July 30, 2020

Abstract

Objective: The potential ability for weather to affect SARS-CoV-2 transmission has been an area of controversial discussion during the COVID-19 pandemic. Individuals’ perceptions of the impact of weather can inform their adherence to public health guidelines; however, there is no measure of their perceptions. We quantified Twitter users’ perceptions of the effect of weather and analyzed how they evolved with respect to real-world events and time.

Materials and Methods: We collected 166,005 tweets posted between January 23 and June 22, 2020 and employed machine learning/natural language processing techniques to filter for relevant tweets, classify them by the type of effect they claimed, and identify topics of discussion.

Results: We identified 28,555 relevant tweets and estimate that 40.4% indicate uncertainty about weather’s impact, 33.5% indicate no effect, and 26.1% indicate some effect. We tracked changes in these proportions over time. Topic modeling revealed major latent areas of discussion.

Discussion: There is no consensus among the public for weather’s potential impact. Earlier months were characterized by tweets that were uncertain of weather’s effect or claimed no effect; later, the portion of tweets claiming some effect of weather increased. Tweets claiming no effect of weather comprised the largest class by June. Major topics of discussion included comparisons to influenza’s seasonality, President Trump’s comments on weather’s effect, and social distancing.

Conclusion: There is a major gap between scientific evidence and public opinion of weather’s impacts on COVID-19. We provide evidence of public’s misconceptions and topics of discussion, which can inform public health communications.

Suggested Citation

Gupta, Marichi and Bansal, Aditya and Jain, Bhav and Rochelle, Jillian and Oak, Atharv and Jalali, Mohammad S., Whether the Weather Will Help Us Weather the COVID-19 Pandemic: Using Machine Learning to Measure Twitter Users’ Perceptions (July 30, 2020). Available at SSRN: https://ssrn.com/abstract=3663947 or http://dx.doi.org/10.2139/ssrn.3663947

Marichi Gupta

Harvard University - Harvard Medical School ( email )

25 Shattuck St
Boston, MA 02115
United States

Aditya Bansal

Indian Institute of Technology (IIT), Delhi ( email )

Hauz Khas
New Delhi
India

Bhav Jain

Massachusetts Institute of Technology (MIT) ( email )

77 Massachusetts Avenue
50 Memorial Drive
Cambridge, MA 02139-4307
United States

Jillian Rochelle

Harvard University - Harvard Medical School ( email )

25 Shattuck St
Boston, MA 02115
United States

Atharv Oak

Massachusetts Institute of Technology (MIT) ( email )

77 Massachusetts Avenue
50 Memorial Drive
Cambridge, MA 02139-4307
United States

Mohammad S. Jalali (Contact Author)

Harvard University - Harvard Medical School ( email )

101 Merrimac St
Suite 1010
Boston, MA 02114
United States

HOME PAGE: http://scholar.harvard.edu/jalali

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