RESEARCHING METHODS FOR THE AUTOMATIC DETECTION OF OFFENSIVE LANGUAGE BASED ON ARTIFICIAL INTELLIGENCE
DOI:
https://doi.org/10.5281/zenodo.22701354Abstract
This study explores artificial intelligence-based methods for the automatic detection of offensive language.
The research focuses on the application of Natural Language Processing (NLP), machine learning, and deep learning
techniques to identify offensive, abusive, and inappropriate content in textual data. Particular attention is given to text preprocessing,
feature extraction, text classification, and neural network-based approaches for improving the accuracy and
efficiency of offensive language detection. The study highlights the potential of artificial intelligence to support safer digital
communication and enhance automated content moderation across online platforms
Keywords
Artificial intelligence, offensive language detection, natural language processing, machine learning, deep learning, neural networks, text classification, sentiment analysis, automated content moderation, abusive language, language models, social media.References
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