Hate speech towards female game players in Valorant game

This study examined the types of hate speech towards female game players in Valorant on the North American (NA) server. The data was collected from 36 videos (out of 1,254) from seven female YouTube channels between 2020 and 2023, where hate speech occurred during gameplay. This study utilizes a combination of quantitative and qualitative research methods. The researchers created precoding schemes based on Bahador’s (2023) framework of hate speech. Moreover, the researchers identified types of discrimination reflected through hate speech inspired by Kowert’s (2020) model. The findings show that the most common type of hate speech was “Negative character” (37%), followed by “Disagreement” (24%) and “Negative action” (20%). Less frequent types included “Demonizing and Dehumanizing” (16%), while “Death” and “Violence” each appeared in only 1% of cases. Five types of discrimination were identified: Offensive name calling, Trolling/Griefing, Sexual harassment, Sexual assault, and Threats of physical violence. Notably, instances of hate speech can be categorized into more than one type of discrimination categories. These findings highlight the current state of online gaming, particularly the discrimination faced by female game players. They can raise awareness among victims, parents, influencers, and the gaming industry to detect hate speech effectively.

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Publication Details

Journal
Journal of English Language and Linguistics
Published
2024-12-20
DOI
https://doi.org/10.62819/jel.2024.657
Primary Topic
Multimedia Learning Systems
Type
article
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article

Hate speech towards female game players in Valorant game

Sutraphorn Tantiniranat, Wirakarn Pornying
Journal of English Language and Linguistics
Multimedia Learning Systems
article

Hate speech towards female game players in Valorant game

Sutraphorn Tantiniranat, Wirakarn Pornying
article en

Abstract

This study examined the types of hate speech towards female game players in Valorant on the North American (NA) server. The data was collected from 36 videos (out of 1,254) from seven female YouTube channels between 2020 and 2023, where hate speech occurred during gameplay. This study utilizes a combination of quantitative and qualitative research methods. The researchers created precoding schemes based on Bahador’s (2023) framework of hate speech. Moreover, the researchers identified types of discrimination reflected through hate speech inspired by Kowert’s (2020) model. The findings show that the most common type of hate speech was “Negative character” (37%), followed by “Disagreement” (24%) and “Negative action” (20%). Less frequent types included “Demonizing and Dehumanizing” (16%), while “Death” and “Violence” each appeared in only 1% of cases. Five types of discrimination were identified: Offensive name calling, Trolling/Griefing, Sexual harassment, Sexual assault, and Threats of physical violence. Notably, instances of hate speech can be categorized into more than one type of discrimination categories. These findings highlight the current state of online gaming, particularly the discrimination faced by female game players. They can raise awareness among victims, parents, influencers, and the gaming industry to detect hate speech effectively.

Journal of English Language and LinguisticsVol. 5(3)
Burapha University (TH)
Gender equality
Openalex Percentile: Top 62%
Multimedia Learning Systems
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Hate speech towards female game players in Valorant game — Sutraphorn Tantiniranat, Wirakarn Pornying · Journal of English Language and Linguistics (2024) | TGRS Research Map | TGRS