From prejudice to marginalization: Tracing the forms of online hate speech targeting LGBTQ+ and Muslim communities

This study investigates online hate speech in Finland, particularly Twitter messages targeting people of Muslim faith and the LGBTQ+ community, using a mixed-methods approach that combines quantitative text classification with a BERT model and qualitative thematic analysis via BERTopic and examination of highly interacted posts from 2018 to 2023. The study shows increasing instances of hate speech occurring online, primarily against Muslims, with topic modeling uncovering 32 topics for Muslims and 41 for the LGBTQ+ community, featuring themes of violence, cultural conflict, and challenges to traditional values. The LGBTQ+ community is depicted as undermining traditional norms, whereas Muslims are presented with hostility. The research underscores the necessity for digital platforms to employ nuanced strategies to counter hate speech, advocating for policies that tackle hate speech while also addressing the underlying factors and enhancing understanding of the social and cultural contexts of the targeted groups to refine detection accuracy.

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Publication Details

Journal
New Media & Society
Published
2025-01-16
DOI
https://doi.org/10.1177/14614448241312900
Citations
3
Primary Topic
Hate Speech and Cyberbullying Detection
Type
article
Field-Weighted Citation Impact
7.44

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article

From prejudice to marginalization: Tracing the forms of online hate speech targeting LGBTQ+ and Muslim communities

Ali Ünlü, Nitin Sawhney, Tuukka Tammi, Tommi Kotonen et al.
3 citations
New Media & Society
Hate Speech and Cyberbullying Detection
7.44
article

From prejudice to marginalization: Tracing the forms of online hate speech targeting LGBTQ+ and Muslim communities

Ali Ünlü, Nitin Sawhney, Tuukka Tammi, Tommi Kotonen, Sophie Truong
article en
3 citations

Abstract

This study investigates online hate speech in Finland, particularly Twitter messages targeting people of Muslim faith and the LGBTQ+ community, using a mixed-methods approach that combines quantitative text classification with a BERT model and qualitative thematic analysis via BERTopic and examination of highly interacted posts from 2018 to 2023. The study shows increasing instances of hate speech occurring online, primarily against Muslims, with topic modeling uncovering 32 topics for Muslims and 41 for the LGBTQ+ community, featuring themes of violence, cultural conflict, and challenges to traditional values. The LGBTQ+ community is depicted as undermining traditional norms, whereas Muslims are presented with hostility. The research underscores the necessity for digital platforms to employ nuanced strategies to counter hate speech, advocating for policies that tackle hate speech while also addressing the underlying factors and enhancing understanding of the social and cultural contexts of the targeted groups to refine detection accuracy.

New Media & SocietyVol. 28(3)
Finnish Institute for Health and Welfare (FI), Finland University (FI), University of Virginia (US), University of Jyväskylä (FI), Aalto University (FI)
Aalto-Yliopisto, Jyväskylän Yliopisto
Openalex Percentile: Top 4%
Hate Speech and Cyberbullying Detection
7.44
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From prejudice to marginalization: Tracing the forms of online hate speech targeting LGBTQ+ and Muslim communities — Ali Ünlü, Nitin Sawhney, et al. · New Media & Society (2025) | TGRS Research Map | TGRS