Scholarlink

<p>The COVID-19 pandemic has brought significant challenges to the global healthcare system and has fueled the spread of numerous rumors, deceptions, and fake news. The main objective of this work is to investigate, design, and apply an intelligent computational model to identify fake news related to the health area, focusing on the COVID-19 infodemic. The MFAKES method was applied in a case study using three news datasets on the COVID-19 pandemic. The results show that the proposed method obtained promising results in detecting fake news, as evaluated by the metrics of accuracy, precision, recall, and F1 score. The models achieved an accuracy of up to 93% in identifying fake news. The contributions of this work are significant for combating disinformation and providing a basis for fake news detection systems. In addition to improving accuracy in the identification of disinformation, the MFAKES method stands out for its practicality and scalability, making it adaptable for widespread use.</p>

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

MFAKES: A Method for Fake News Analysis in Healthcare Area Focusing on COVID-19

  • 期刊论文

  • 发表日期：

    2025年9月17日

查看全文
  • Samara Cardoso dos Santos,
  • Erik Miguel de Elias,
  • Johnny Cardoso Marques,
  • Adilson Marques da Cunha

摘要

The COVID-19 pandemic has brought significant challenges to the global healthcare system and has fueled the spread of numerous rumors, deceptions, and fake news. The main objective of this work is to investigate, design, and apply an intelligent computational model to identify fake news related to the health area, focusing on the COVID-19 infodemic. The MFAKES method was applied in a case study using three news datasets on the COVID-19 pandemic. The results show that the proposed method obtained promising results in detecting fake news, as evaluated by the metrics of accuracy, precision, recall, and F1 score. The models achieved an accuracy of up to 93% in identifying fake news. The contributions of this work are significant for combating disinformation and providing a basis for fake news detection systems. In addition to improving accuracy in the identification of disinformation, the MFAKES method stands out for its practicality and scalability, making it adaptable for widespread use.