AUTHOR=Tsao Shu-Feng , MacLean Alexander , Chen Helen , Li Lianghua , Yang Yang , Butt Zahid Ahmad 

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

JOURNAL=International Journal of Public Health

VOLUME=Volume 67 - 2022

YEAR=2022

URL=https://www.ssph-journal.org/journals/international-journal-of-public-health/articles/10.3389/ijph.2022.1604658

DOI=10.3389/ijph.2022.1604658

ISSN=1661-8564

ABSTRACT=The COVID-19 pandemic has continued for over a year and caused a significant number of cases and deaths in Canada. Governments have implemented lockdowns to reduce the transmission. This study aims to explore topics and sentiments using tweets from Ontario, Canada, during its second wave and identify any correlation between public attitude and government policy and cases. Tweets were collected from December 5, 2020, to March 6, 2021, with locations in Toronto and Ottawa, excluding accounts from organizations and individual political figures. Latent Dirichlet Allocation was used for unsupervised topic modeling. Valence Aware Dictionary and sEntiment Reasoner was used to calculate daily and average sentiment compound scores for topics identified. Vaccine, pandemic, business, lockdown, mask, and Ontario were 6 topics identified from the unsupervised topic modeling. Our study results have shown a slightly positive sentiment on average during the second wave of the COVID-19 pandemic in Ontario. Our research has also demonstrated a possible social listening approach to identify what the public sentiments and opinions are in a timely manner using a combination of quantitative and qualitative methods.