MINI REVIEW article
Front. Commun.
Sec. Media Governance and the Public Sphere
Volume 10 - 2025 | doi: 10.3389/fcomm.2025.1603534
AI-Based Disinformation and Hate Speech Amplification: Analysis of Indonesia's Digital Media Ecosystem
Provisionally accepted
- Communication Sciences, Faculty of Social and Political Sciences, Hasanuddin University, Makassar, South Sulawesi, Indonesia
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The development of artificial intelligence (AI) has significantly transformed Indonesia's digital media ecosystem, including how disinformation and hate speech are produced, disseminated, and consumed. This short review critically analyzes how AI technologies contribute to hate speech amplification in Indonesia through a comprehensive literature examination from 2018-2024. Using a systematic methodology, we identify three primary mechanisms: (1) content production automation that facilitates large-scale dissemination of hate-laden messages, (2) content personalization that creates echo chambers and reinforces polarization, and (3) multimodal manipulation that enhances the credibility of misleading content. Regional analysis across 15 Indonesian provinces reveals geographic variations in the dissemination patterns and impact of AI-based disinformation, with urban areas showing higher vulnerability to sophisticated visual manipulation. In contrast, rural areas are more susceptible to textual disinformation. This study identifies significant gaps in current research, including a limited understanding of the effectiveness of various intervention strategies in the Indonesian context, a lack of culturally sensitive AI models for detecting hate speech in regional languages, and a scarcity of longitudinal studies on long-term impacts. We suggest future development directions, emphasizing the importance of cross-disciplinary collaboration between linguists, computer scientists, and media researchers to develop solutions considering Indonesia's socio-cultural context.
Keywords: artificial intelligence, disinformation, Hate speech, Indonesian digital media, Regional analysis, Deepfake
Received: 01 Apr 2025; Accepted: 20 Aug 2025.
Copyright: © 2025 Febri Sonni. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Alem Febri Sonni, Communication Sciences, Faculty of Social and Political Sciences, Hasanuddin University, Makassar, South Sulawesi, Indonesia
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