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The rampant spread of fake news has adversely affected society, resulting inextensive research on curbing its spread. As a notable milestone in largelanguage models (LLMs), ChatGPT has gained significant attention due to itsexceptional natural language processing capabilities. In this study, we presenta thorough exploration of ChatGPT's proficiency in generating, explaining, anddetecting fake news as follows. Generation -- We employ four prompt methods togenerate fake news samples and prove the high quality of these samples throughboth self-assessment and human evaluation. Explanation -- We obtain ninefeatures to characterize fake news based on ChatGPT's explanations and analyzethe distribution of these factors across multiple public datasets. Detection --We examine ChatGPT's capacity to identify fake news. We explore its detectionconsistency and then propose a reason-aware prompt method to improve itsperformance. Although our experiments demonstrate that ChatGPT showscommendable performance in detecting fake news, there is still room for itsimprovement. Consequently, we further probe into the potential extrainformation that could bolster its effectiveness in detecting fake news.

Harnessing the Power of ChatGPT in Fake News: An In-Depth Exploration in Generation, Detection and Explanation