Reading Twitter as a marketplace of ideas: how attitudes to COVID-19 are affecting attitudes to migrants in Ireland
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Stephen Lucek
und
Dean Phelan
Abstract
Attitudes to language and attitudes to ethnic groups have long been shown to be related to one another. In recent history, significant events have also been shown to negatively affect attitudes to specific groups who are deemed to be responsible. The current paper looks at how the COVID-19 pandemic has emboldened those who hold far right attitudes to migrants in an Irish context. Through a Twitter scraping exercise, conducted in August 2020, we show that far right framings of migrants as (a) contagion or disease, (b) criminals, and (c) favoured or elites are clearly evident and considerably on the rise in these Irish data. This would seem to run contrary to a concurrent study in Germany. Thus, we then pair this quantitative Twitter data with qualitative observations of anti-mask protests as indicative of a broadening of the allure of far right political groups, with COVID-19 as the “leading edge”. Taken together, these data seem to run contrary to European Social Survey and comparative data, leading us to question how attitudes are elicited, measured, and reported.
Funding source: Enterprise Ireland H2020 Proposal Preparation Support
Award Identifier / Grant number: CS20192141
Acknowledgments
We would like to thank the co-editors of this special issue of Linguistics Vanguard for bringing us all together in an effort to continue our work during the Covid-19 pandemic. We also thank the anonymous reviewers whose helpful comments and suggestions improved this paper immensely.
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Research funding: We are grateful to Enterprise Ireland for their generous seed funding support for this research, the Universitas 21 Researcher Relief Fund and the Getting Data Working Group (Amsterdam) for research support funding (in addition to moral support to the authors during a very difficult time for us all).
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© 2024 Walter de Gruyter GmbH, Berlin/Boston
Artikel in diesem Heft
- Frontmatter
- Research Articles
- Getting “good” data in a pandemic, part 2: more tools in the toolbox
- Reading Twitter as a marketplace of ideas: how attitudes to COVID-19 are affecting attitudes to migrants in Ireland
- Collecting language assessment data in the age of pandemic: a preliminary case study of Chinese EFL learners
- Investigating the relationship between the speed of automatization and linguistic abilities: data collection during the COVID-19 pandemic
- Gettin’ sociolinguistic data remotely: comparing vernacularity during online remote versus in-person sociolinguistic interviews
- Bear in a Window: collecting Australian children’s stories of the COVID-19 pandemic
- Re-taking the field: resuming in-person fieldwork amid the COVID-19 pandemic
Artikel in diesem Heft
- Frontmatter
- Research Articles
- Getting “good” data in a pandemic, part 2: more tools in the toolbox
- Reading Twitter as a marketplace of ideas: how attitudes to COVID-19 are affecting attitudes to migrants in Ireland
- Collecting language assessment data in the age of pandemic: a preliminary case study of Chinese EFL learners
- Investigating the relationship between the speed of automatization and linguistic abilities: data collection during the COVID-19 pandemic
- Gettin’ sociolinguistic data remotely: comparing vernacularity during online remote versus in-person sociolinguistic interviews
- Bear in a Window: collecting Australian children’s stories of the COVID-19 pandemic
- Re-taking the field: resuming in-person fieldwork amid the COVID-19 pandemic
