DEVELOPING AN ARTIFICIAL INTELLIGENCE MODEL FOR DETECTING TOXIC (HARMFUL) CONTENT IN TEXTS

The article analyzes the theoretical and methodological foundations of building an artificial intelligence model for the automatic detection of toxic content in texts, namely insulting, degrading, threatening and hate-inciting statements. Taking into account the features of Uzbek as a low-resource language, the parallel use of the Latin and Cyrillic scripts and the phenomenon of code-switching with Russian, a conceptual model architecture for Uzbek-language texts is proposed.

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Publication Details

Journal
International journal of technology and academic research
Published
2026-10-28
Primary Topic
Hate Speech and Cyberbullying Detection
Type
article
Field-Weighted Citation Impact
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article

DEVELOPING AN ARTIFICIAL INTELLIGENCE MODEL FOR DETECTING TOXIC (HARMFUL) CONTENT IN TEXTS

Toshpulatov Javoxir Xamidulla o'g'li
International journal of technology and academic research
Hate Speech and Cyberbullying Detection
article

DEVELOPING AN ARTIFICIAL INTELLIGENCE MODEL FOR DETECTING TOXIC (HARMFUL) CONTENT IN TEXTS

Toshpulatov Javoxir Xamidulla o'g'li
article en

Abstract

The article analyzes the theoretical and methodological foundations of building an artificial intelligence model for the automatic detection of toxic content in texts, namely insulting, degrading, threatening and hate-inciting statements. Taking into account the features of Uzbek as a low-resource language, the parallel use of the Latin and Cyrillic scripts and the phenomenon of code-switching with Russian, a conceptual model architecture for Uzbek-language texts is proposed.

International journal of technology and academic research
Openalex Percentile: Top 13%
Hate Speech and Cyberbullying Detection
Open Access PDFOpenAlex
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DEVELOPING AN ARTIFICIAL INTELLIGENCE MODEL FOR DETECTING TOXIC (HARMFUL) CONTENT IN TEXTS — Toshpulatov Javoxir Xamidulla o'g'li · International journal of technology and academic research (2026) | TGRS Research Map | TGRS