Topic modelling of Far-right Canadians’ tweets on COVID-19
| dc.contributor.author | Al-Rawi, Ahmed | |
| dc.date.accessioned | 2023-01-27T16:26:57Z | |
| dc.date.available | 2023-01-27T16:26:57Z | |
| dc.date.issued | 2022-05 | |
| dc.description.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). | en_US |
| dc.identifier.uri | http://hdl.handle.net/10315/40845 | |
| dc.language.iso | en | en_US |
| dc.subject | Race | |
| dc.subject | COVID-19 | |
| dc.subject | Social media | |
| dc.subject | Pandemic | |
| dc.subject | ||
| dc.title | Topic modelling of Far-right Canadians’ tweets on COVID-19 | en_US |
| dc.type | Conference Paper | en_US |