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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.
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.
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. Yet, the vast majority of this type of work is done 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 towards vaccine-related topics. METHODS Comments made on posts providing regular updates on COVID-19 statistics in the Vancouver, Toronto, and Calgary subreddits (r/vancouver, r/toronto, r/calgary) between July 13th, 2020 and June 14th, 2021 were extracted (N = 49,291, 20,764, and 21,277, respectively). Latent Dirichlet allocation was used to identify frequently discussed topics. Sentiment (joy, sadness, fear, and anger) scores were assigned to comments using random forest regression. RESULTS Beginning by focusing on the Vancouver subreddit, the number of comments made on each post positively correlated with the number of new cases (P < 0.001). From the comments, thirteen topics were identified. Two were related to vaccines, one regarding vaccine uptake and the other about vaccine supply. The levels of discussion for both topics were linked to the total number of vaccinations given (Granger test for causality: P < 0.001). Comments pertaining to either topic displayed higher scores for joy compared to comments about other topics (P < 0.001). Calgary and Toronto also discussed vaccine uptake. Sentiment scores for this topic differed across the three cities (P < 0.001). CONCLUSIONS Overall, our work demonstrates that comments from Reddit can be used to better understand concerns and sentiments surrounding the pandemic at the local level, which enables more targeted and publicly-acceptable policies.
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