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<p>The paper investigates a phenomenon of fake messages and approaches to their detection. It presents a comparative analysis of the effectiveness of using different neural network models for the problems of searching and classifying text fragments containing fake messages. The paper also studies the influence of the model’s dimension on the learning speed, detection accuracy, and ability to adapt to unknown data.</p>

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Comparative Analysis of Neural Network Models for Text Classification Problems

  • 期刊论文

  • 发表日期：

    2025年5月30日

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  • A. V. Anisimov,
  • O. O. Marchenko,
  • E. M. Nasirov,
  • V. Y. Taranukha

摘要

The paper investigates a phenomenon of fake messages and approaches to their detection. It presents a comparative analysis of the effectiveness of using different neural network models for the problems of searching and classifying text fragments containing fake messages. The paper also studies the influence of the model’s dimension on the learning speed, detection accuracy, and ability to adapt to unknown data.