Background During the COVID-19 pandemic in Canada, Prime Minister Justin Trudeau provided updates on the novel coronavirus and the government’s responses to the pandemic in his daily briefings from March 13 to May 22, 2020, delivered on the official Canadian Broadcasting Corporation (CBC) YouTube channel. Objective The aim of this study was to examine comments on Canadian Prime Minister Trudeau’s COVID-19 daily briefings by YouTube users and track these comments to extract the changing dynamics of the opinions and concerns of the public over time. Methods We used machine learning techniques to longitudinally analyze a total of 46,732 English YouTube comments that were retrieved from 57 videos of Prime Minister Trudeau’s COVID-19 daily briefings from March 13 to May 22, 2020. A natural language processing model, latent Dirichlet allocation, 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 Prime Minister Trudeau’s policies, essential work and frontline workers, individuals’ financial challenges, rental and mortgage subsidies, quarantine, government financial aid for enterprises and individuals, personal protective equipment, Canada and China’s relationship, vaccines, and reopening. Conclusions This study is the first to longitudinally investigate public discourse and concerns related to Prime Minister Trudeau’s daily COVID-19 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 future health emergencies.
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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