Public Attitudes During the Second Lockdown: Sentiment and Topic Analyses Using Tweets From Ontario, Canada

Area of Science:

• Public Health
• Social Media Analysis
• Computational Social Science

Background:

• The second wave of the COVID-19 pandemic presented significant public health challenges.
• Social media platforms like Twitter serve as a vital source for understanding public discourse.
• Monitoring public sentiment is crucial for effective pandemic response.

Purpose of the Study:

• To analyze public topics and sentiments expressed on Twitter in Ontario during the second COVID-19 wave.
• To identify key themes and emotional responses related to the pandemic, vaccines, and public health measures.
• To demonstrate a social listening approach for timely public opinion analysis.

Main Methods:

• Collected tweets from Ontario between December 5, 2020, and March 6, 2021.
• Utilized Latent Dirichlet Allocation for unsupervised topic modeling.
• Employed VADER for sentiment analysis to determine daily and average sentiment scores.

Main Results:

• Six primary topics emerged: vaccine, pandemic, business, lockdown, mask, and Ontario.
• Average sentiment scores across topics were slightly positive.
• Daily sentiment scores exhibited significant fluctuations between positive and negative emotions.

Conclusions:

• Public sentiment in Ontario during the second COVID-19 wave was, on average, slightly positive.
• The study successfully identified key public discussion topics and sentiment trends.
• Social listening provides a valuable tool for real-time public health monitoring and communication.