Investigating the Impacts of Policy Stringency on the Public Perceptions of Pandemic Policies, Sentiment Analysis of Tweets During the Second and Third COVID-19 Pandemic Waves in Ontario

Abstract

Background: Public sentiment plays a critical role in shaping compliance and trust during public health crises. The COVID-19 pandemic was the first example of an infodemic, and the significant amount of social media data from that time period can be useful for understanding public responses and experiences throughout the pandemic. This study explores emotional responses to COVID-19 policy interventions in Ontario, Canada, using Twitter data to assess how public sentiments varied across lockdowns, mask policies, and vaccine mandates. The research aims to understand how policy stringency and a regional context influenced public attitudes throughout the pandemic. Methods: Data from the Twitter API was collected and analysed. Tweets posted between December 1st, 2020 and June 30th, 2021 from app users in Ontario were compiled and sorted using zero-shot classification into subgroups for relevant categories – vaccine mandates, mask policies, and lockdown measures. These tweets were then analyzed using sentiment analysis and the COVID-19 Stringency Index to identify trends in the sentiments expressed on Twitter over time, considering changes in the strictness of various pandemic measures. Results: Initial temporal analysis identified key events that led to notable sentiment changes, such as sentiment spikes following the announcement of the CERB program in March, followed by lockdown sentiments declining sharply in April after the use of the “provincial emergency brake”. Lockdown sentiments remained consistently neutral to negative, with no significant threshold effects or time-based recovery. Vaccine mandates showed a positive shift in sentiment beyond identified stringency breakpoints, with further improvement over time. Mask mandates initially received positive sentiments but declined sharply after passing a stringency threshold. Ottawa Twitter users expressed more positive and emotionally reactive sentiment than Toronto users, particularly in response to lockdown and vaccine policies. Conclusion: Social media data offers valuable insight into public sentiment dynamics during health emergencies. Findings suggest that policy framing and perceived intrusiveness significantly influence emotional responses, with vaccine mandates benefiting from proactive messaging and civic framing. Regional differences underscore the importance of localized communication strategies. These results can inform future public health interventions by emphasizing the role of timing, tone, and threshold sensitivity in shaping public trust and engagement.