Faculty of Information, University of Toronto, Toronto, ON, Canada.
Factor Inwentash Faculty of Social Work, University of Toronto, Toronto, ON, Canada.
J Med Internet Res. 2021 Feb 23;23(2):e23957. doi: 10.2196/23957.
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.
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.
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.
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.
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.
在加拿大 COVID-19 大流行期间，总理贾斯汀·特鲁多（Justin Trudeau）于 2020 年 3 月 13 日至 5 月 22 日期间在加拿大广播公司（CBC）的官方 YouTube 频道上发布了每日简报，介绍新型冠状病毒以及政府对大流行的应对措施。
本研究旨在检查 YouTube 用户对加拿大总理特鲁多 COVID-19 每日简报的评论，并跟踪这些评论以提取公众意见和关注点随时间变化的动态。
我们使用机器学习技术对 2020 年 3 月 13 日至 5 月 22 日期间从特鲁多总理的 57 个 COVID-19 每日简报视频中检索到的总计 46,732 条英文 YouTube 评论进行了纵向分析。自然语言处理模型潜在狄利克雷分配（Latent Dirichlet Allocation）用于选择每个视频中采样评论中的突出主题。主题分析用于将这些突出主题分类并总结为不同的主要主题。
我们发现了 11 个突出的主题，包括严格的边境措施、公众对特鲁多总理政策的反应、基本工作和前线工人、个人的财务挑战、租金和抵押贷款补贴、隔离、政府对企业和个人的财政援助、个人防护设备、加拿大与中国的关系、疫苗和重新开放。
这项研究首次纵向调查了与加拿大总理特鲁多 COVID-19 每日简报相关的公众言论和关注点。这项研究为在社交媒体上建立公众与公共卫生官员之间的实时反馈循环做出了贡献。听取和回应公众的真实关切可以增强政府与公众之间的信任，为未来的卫生应急做好准备。
