Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Aug 30, 2020
Date Accepted: Feb 4, 2021
Date Submitted to PubMed: Feb 5, 2021
Commenting on PM Trudeau’s COVID-19 daily briefing in Canada: data mining public opinions and concerns on YouTube
ABSTRACT
Background:
During the COVID-19 pandemic in Canada, Prime Minister Justin Trudeau has provided updates on the noval coronavirus and government’s responses in his daily briefings from March 13 to May 22, 2020, delivered on the CBC official YouTube channel (Canadian Broadcasting Corporation).
Objective:
This study aims to examine and track YouTube users’ comments on PM Trudeau’s COVID-19 daily briefings in Canada over time.
Methods:
We used machine learning techniques and longitudinally analyzed a total of 46,732 English YoutTube comments retrieved from 57 videos of PM Trudeau’s COVID-19 daily briefings from March 13 to May 22, 2020. The natural language processing, Latent Dirichlet Allocation (LDA) model was used to choose salient topics among the sampled comments in each of the single days. Thematic analysis was used to classify and summarize these salient topics into different prominent themes.
Results:
We found 11 prominent themes, including “strict border measures,” “public responses to PM Trudeau’s policies,” “essential work and frontline workers,” “individuals’ financial challenges,” “rental and mortgage bursary,” “quarantine,” “government financial aid for enterprises and individuals,” “PPE,” “Canada and China relationship,” “vaccine,” and “re-opening.”
Conclusions:
The present study is the first to longitudinally investigate public discourse and concerns of PM Trudeau’s COVID-19 daily briefings in Canada. This study contributes to the establishment of a real-time feedback loop between the public and public health officials on YouTube. Hearing and reacting to real concerns from the public can enhance trust between the government and the public to prepare for a future health emergency.
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