Investigating Hate Speech Comments: A Forensic Linguistic Study

The meaning of hate speech in social media can shift because the way people use social media is constantly changing, and the social and political context in which social media is used can also change. This study aims to analyze hate speech comments on Instagram and the meaning and relevance of the implicature to forensic linguistics. This research employs a qualitative approach to collect and analyze the meaning of hate speech. The research data was obtained from Instagram through hashtag searches. The main findings of this study indicate that hate speech on social media tends to avoid direct vulgar linguistic forms and instead relies on implicit language strategies to convey negative sentiments towards individuals or groups. There is widespread use of diminutives such as “bocah” or “bocil,” social stigmatization such as “ndeso” and “bau kencur,” and institutional euphemisms such as “makkamah keluarga,” all of which are important linguistic indicators in the analysis of political hatred in the digital space. The intensity classification shows that hate speech with moderate and severe intensity does not only come from explicit insults but also from narratives that normalize harassment based on age, appearance, and political affiliation. The implications of this study indicate that a forensic linguistic approach is very effective in uncovering forms of hate speech disguised through language strategies such as sarcasm, stereotypes, and euphemisms. Theoretically, these findings enrich the study of pragmatic linguistics and speech acts by showing the importance of implicature analysis in detecting non-explicit hate intentions.

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Publication Details

Journal
Austronesian Journal of Language Science & Literature
Published
2025-04-05
DOI
https://doi.org/10.59011/austronesian.4.1.2025.47-64
Primary Topic
Hate Speech and Cyberbullying Detection
Type
article
Field-Weighted Citation Impact
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article

Investigating Hate Speech Comments: A Forensic Linguistic Study

Rika Purnama Sari, Muhammad Kamal Bin Abdul Hakim, Miftahulkhairah Anwar
Austronesian Journal of Language Science & Literature
Hate Speech and Cyberbullying Detection
article

Investigating Hate Speech Comments: A Forensic Linguistic Study

Rika Purnama Sari, Muhammad Kamal Bin Abdul Hakim, Miftahulkhairah Anwar
article en

Abstract

The meaning of hate speech in social media can shift because the way people use social media is constantly changing, and the social and political context in which social media is used can also change. This study aims to analyze hate speech comments on Instagram and the meaning and relevance of the implicature to forensic linguistics. This research employs a qualitative approach to collect and analyze the meaning of hate speech. The research data was obtained from Instagram through hashtag searches. The main findings of this study indicate that hate speech on social media tends to avoid direct vulgar linguistic forms and instead relies on implicit language strategies to convey negative sentiments towards individuals or groups. There is widespread use of diminutives such as “bocah” or “bocil,” social stigmatization such as “ndeso” and “bau kencur,” and institutional euphemisms such as “makkamah keluarga,” all of which are important linguistic indicators in the analysis of political hatred in the digital space. The intensity classification shows that hate speech with moderate and severe intensity does not only come from explicit insults but also from narratives that normalize harassment based on age, appearance, and political affiliation. The implications of this study indicate that a forensic linguistic approach is very effective in uncovering forms of hate speech disguised through language strategies such as sarcasm, stereotypes, and euphemisms. Theoretically, these findings enrich the study of pragmatic linguistics and speech acts by showing the importance of implicature analysis in detecting non-explicit hate intentions.

Austronesian Journal of Language Science & LiteratureVol. 4(1)
State University of Jakarta (ID)
Openalex Percentile: Top 92%
Hate Speech and Cyberbullying Detection
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