Method for Protecting Users From Fake News Using Hybrid Evaluation Methods Combining Artificial Intelligence and User Experience

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This research demonstrates a hybrid system improving classification accuracy of fake news in users, suggesting enhanced media literacy is crucial.

The neural network achieved a classification accuracy of 84%, indicating effectiveness in detecting disinformation.
Qualitative analysis revealed that fake news thrives on emotional appeal and simplicity, often linked to political topics.
A hybrid approach combining artificial intelligence and user expertise was developed to assess and combat fake news.
This research highlights the need for user education and ongoing improvements to techniques for countering fake news.

Buchwald et al. (2025) studied this question.

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This research demonstrates a hybrid system improving classification accuracy of fake news in users, suggesting enhanced media literacy is crucial.