An Analysis of Netizens’ Hate Comments Toward Joe Biden’s Speech “Biden Delivers Memorial Day Message” on Fox News’s YouTube Channel
DOI:
https://doi.org/10.32493/pnp.v4i1.58531Keywords:
bias, comment, hate, speech, toxicityAbstract
This study aims to examine how social bias and toxicity are manifested in hate speech directed at Joe Biden’s speech on YouTube. The object of this study is the comments section of the video entitled “Biden Delivers Memorial Day Message” published in 2024 on Fox News’s YouTube channel. This study employs a qualitative descriptive method, with data collected through in-depth reading and analysis of words, phrases, and sentences found in the comments. The study applies Won’s theory (2001), which identifies two types of bias—gender bias and other biases—and three types of toxicity: hate, insult, and offensive expression. The findings reveal that 11 instances of bias were identified in the comments, with “other biases” being the most dominant type. Additionally, 69 instances of toxicity were found, with insults emerging as the most frequent category. The dominance of other biases and insults suggests that hate comments on social media tend to focus on personal attacks against the speaker as a way of expressing anger and hostility, rather than critically engaging with the content of the speech itself.
References
Auwal, A. M. (2018). Social media and hate speech: Analysis of comments on Biafra agitations, Arewa youths’ ultimatum and their implications on peaceful coexistence in Nigeria. Media and Communication Currents, 2(1), 54–74.
Banik, N., & Rahman, M. H. H. (2019, December). Toxicity detection on Bengali social media comments using supervised models. In 2019 International Conference on Innovation in Engineering and Technology (ICIET) (pp. 1–5). IEEE.
Calderón, F. H., Balani, N., Taylor, J., Peignon, M., Huang, Y. H., & Chen, Y. S. (2021). Linguistic patterns for code word resilient hate speech identification. Sensors, 21(23), 7859. https://doi.org/10.3390/s21237859
Cho, W. I., & Moon, J. (2021, December). How does the hate speech corpus concern sociolinguistic discussions? A case study on Korean online news comments. In Proceedings of the Workshop on Natural Language Processing for Digital Humanities (pp. 13–22).
Creswell, J. W., Hanson, W. E., Clark Plano, V. L., & Morales, A. (2007). Qualitative research designs: Selection and implementation. The Counseling Psychologist, 35(2), 236–264. https://doi.org/10.1177/0011000006287390
Danesi, M. (2017). Language, society, and new media: Sociolinguistics today. Routledge.
Fadhilah, N., Suswanto, B., & Utami, Y. P. (2023). Forensic linguistics: Netizens' hate speech implicature on the issue of the 2024 presidential election (TikTok social media case study). Technium Social Sciences Journal, 50, 204–214.
Fan, H., Du, W., Dahou, A., Ewees, A. A., Yousri, D., Elaziz, M. A., & Al-qaness, M. A. (2021). Social media toxicity classification using deep learning: Real-world application UK Brexit. Electronics, 10(11), 1332. https://doi.org/10.3390/electronics10111332
Gumperz, J. J., & Cook-Gumperz, J. (2008). Studying language, culture, and society: Sociolinguistics or linguistic anthropology? Journal of Sociolinguistics, 12(4), 532–545.
Howard, J. W. (2019). Free speech and hate speech. Annual Review of Political Science, 22, 93–109. https://doi.org/10.1146/annurev-polisci-051517-012343
Husda, A., & Saragih, E. L. L. (2021). Taboo words in hate speech through social media. Technium Social Sciences Journal, 17, 510–517.
Jaspal, R., & Coyle, A. (2009). Reconciling social psychology and sociolinguistics: Language and identity among second-generation British Asians. British Journal of Social Psychology, 48(3), 505–521.
Kunst, M., Porten-Cheé, P., Emmer, M., & Eilders, C. (2021). Do “good citizens” fight hate speech online? Effects of solidarity citizenship norms on user responses to hate comments. Journal of Information Technology & Politics, 18(3), 258–273. https://doi.org/10.1080/19331681.2020.1871142
Pedersen, R. T., Petersen, N. B. G., & Thau, M. (2025). Online abuse of politicians: Experimental evidence on politicians’ own perceptions. Political Behavior, 47(1), 119–139.
Romaine, S. (2000). Language in society: An introduction to sociolinguistics. Oxford University Press.
Saleh, H., Alhothali, A., & Moria, K. (2023). Detection of hate speech using BERT and hate speech word embedding with deep model. Applied Artificial Intelligence, 37(1). https://doi.org/10.1080/08839514.2023.2166719
Tahir, I., & Ramadhan, M. G. F. (2024). Hate speech on social media: Indonesian netizens’ hate comments of presidential talk show on YouTube. LLT Journal: A Journal on Language and Language Teaching, 27(1), 230–251.
Wiana, D. (2019). Analysis of the use of hate speech in social media in the case of the 2019 presidential election. Journal of Applied Studies in Language, 3(2), 158–167.
Yule, G. (2022). The study of language (7th ed.). Cambridge University Press.
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