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Topic modelling of Far-right Canadians’ tweets on COVID-19

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Date

2022-05

Authors

Al-Rawi, Ahmed

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Abstract

In this study, I empirically explore the public discourses around the pandemic by far-fight Canadians. I collected 134,739 tweets in September and October 2021 just a few months before the Truckers’ protest in Ottawa. These tweets were posted by 14 Canadian far-right sympathizers or supporters, representing all the available tweets (Table 1). Then, I used a Python program to search for words like “virus”, “covid*”, “corona*”, and extracted 2,555 tweets. Next, I automatedly analyzed the tweets based on topic modelling, which is a machine learning method (Table 2).

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Keywords

Race, COVID-19, Social media, Pandemic, Twitter

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