Comparing Public Sentiment Toward COVID-19 Vaccines Across Canadian Cities: Analysis of Comments on Reddit

Cathy Yan · Melanie Law · Stephanie Nguyen · Jude Dzevela Kong

46 citations0/0 files storedJournal of Medical Internet Research

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Vaccine Coverage and Hesitancy Sentiment Analysis and Opinion Mining Communication and COVID-19 Impact

Abstract

BACKGROUND: Social media enables the rapid consumption of news related to COVID-19 and serves as a platform for discussions. Its richness in text-based data in the form of posts and comments allows researchers to identify popular topics and assess public sentiment. Nonetheless, the vast majority of topic extraction and sentiment analysis based on social media is performed on the platform or country level and does not account for local culture and policies. OBJECTIVE: The aim of this study is to use location-based subreddits on Reddit to study city-level variations in sentiments toward vaccine-related topics. METHODS: Comments on posts providing regular updates on COVID-19 statistics in the Vancouver (r/vancouver, n=49,291), Toronto (r/toronto, n=20,764), and Calgary (r/calgary, n=21,277) subreddits between July 13, 2020, and June 14, 2021, were extracted. Latent Dirichlet allocation was used to identify frequently discussed topics. Sentiment (joy, sadness, fear, and anger) scores were assigned to comments through random forest regression. RESULTS: The number of comments on the 250 posts from the Vancouver subreddit positively correlated with the number of new daily COVID-19 cases in British Columbia (R=0.51, 95% CI for slope 0.18-0.29; P<.001). From the comments, 13 topics were identified. Two were related to vaccines, 1 regarding vaccine uptake and the other about vaccine supply. The levels of discussion for both topics were linked to the total number of vaccines administered (Granger test for causality, P<.001). Comments pertaining to either topic displayed higher scores for joy than for other topics (P<.001). Calgary and Toronto also discussed vaccine uptake. Sentiment scores for this topic differed across the 3 cities (P<.001). CONCLUSIONS: Our work demonstrates that data from city-specific subreddits can be used to better understand concerns and sentiments around COVID-19 vaccines at the local level. This can potentially lead to more targeted and publicly acceptable policies based on content on social media.

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References

2020Social media and vaccine hesitancy 2020Top Concerns of Tweeters During the COVID-19 Pandemic: Infoveillance Study 2020The causes and consequences of COVID-19 misperceptions: Understanding the role of news and social media 2020Public discourse and sentiment during the COVID 19 pandemic: Using Latent Dirichlet Allocation for topic modeling on Twitter 2020The online anti-vaccine movement in the age of COVID-19 2021The anti-vaccination infodemic on social media: A behavioral analysis 2020Social media can have an impact on how we manage and investigate the COVID-19 pandemic 2010We Predict a Riot?: Public Order Policing, New Media Environments and the Rise of the Citizen Journalist

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