Scholarlink

In the age of rapid information dissemination, open access to data has brought numerous benefits but also led to negative consequences, such as the spread of false information. This paper investigates the effectiveness of machine learning models in detecting fake news, specifically focusing on Bi-directional Encoder Representations from Transformers (BERT). Using large datasets of both real and fake news, it has developed detection techniques capable of distinguishing between reliable and misleading sources. Our approach emphasizes the role of enhanced models and optimized data preprocessing in improving the accuracy of fake news detection. Among the models, BERT demonstrated superior performance in terms of both accuracy and speed. This study underscores the critical role that advanced deep learning models play in mitigating the spread of disinformation and ensuring the integrity of digital information ecosystems.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Advanced Deep Learning for Improved Fake News Detection: A BERT-Based Approach

  • 章节

  • 发表日期：

    2025年

查看全文
  • Kalapraveen Bagadi,
  • Visalakshi Annepu,
  • Adnan N. Jameel Al-Tamimi,
  • Mohammed Al-Shammaa,
  • Deepika rani Sona,
  • M. N. Mohammed,
  • Oday I. Abdullah,
  • Nadica Stojanovic

摘要

In the age of rapid information dissemination, open access to data has brought numerous benefits but also led to negative consequences, such as the spread of false information. This paper investigates the effectiveness of machine learning models in detecting fake news, specifically focusing on Bi-directional Encoder Representations from Transformers (BERT). Using large datasets of both real and fake news, it has developed detection techniques capable of distinguishing between reliable and misleading sources. Our approach emphasizes the role of enhanced models and optimized data preprocessing in improving the accuracy of fake news detection. Among the models, BERT demonstrated superior performance in terms of both accuracy and speed. This study underscores the critical role that advanced deep learning models play in mitigating the spread of disinformation and ensuring the integrity of digital information ecosystems.