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In Journal of medical Internet research ; h5-index 88.0

BACKGROUND : During the COVID-19 pandemic in Canada, Prime Minister Justin Trudeau has provided updates on the noval coronavirus and the 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 examines YouTube users' comments on PM Trudeau's COVID-19 daily briefings in Canada and tracks these comments to extract the changing dynamics of public opinions and concerns over time.

METHODS : We used machine learning techniques and longitudinally analyzed a total of 46,732 English YoutTube comments that were 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 for each of the 57 videos. 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 establishing a real-time feedback loop between the public and public health officials on social media. 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.


Zheng Chengda, Xue Jia, Sun Yumin, Zhu Tingshao