Previously submitted to: Journal of Medical Internet Research (no longer under consideration since Jul 13, 2022)
Date Submitted: May 20, 2022
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Topic Modelling and Sentiment Analysis for Twitter Freedom Convoy 2022 in Canada: An Observational Study
ABSTRACT
Background:
Truck drivers gathered at Ottawa, Canada for “Freedom Convoy” to protest the COVID-19 vaccine mandate that went into effect on in mid-January 2022. The convoy has led to controversies and debates on social media, especially on Twitter.
Objective:
This study aimed to investigate public discourses and sentiments regarding the Freedom Convoy on Twitter.
Methods:
English tweets were retrieved from Twitter API from January 15 to February 14, 2022 when the Freedom Convoy occurred. Unsupervised topic modelling and sentiment analysis were applied to identify topics and sentiments for each topic.
Results:
Five topics has resulted from the topic modelling, including protest rally, support extremes, general convoy support, government, and police. Overall, sentiments for each topic have begun with more positive or negative sentiments but approached to neutral over time.
Conclusions:
The results have shown that sentiments towards the Freedom Convoy generally tended to be positive. Five topics were identified from the data collected, and these topics highly correlated with the events of the convoy. Our study also demonstrated that a mixed approach of unsupervised machine learning techniques and manual validation could generate timely evidence.
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