The abundance of information on social media has increased the necessity of
accurate real-time rumour detection. Manual techniques of identifying and
verifying fake news generated by AI tools are impracticable and time-consuming
given the enormous volume of information generated every day. This has sparked
an increase in interest in creating automated systems to find fake news on the
Internet. The studies in this research demonstrate that the BERT and RobertA
models with fine-tuning had the best success in detecting AI generated news.
With a score of 98%, tweaked RobertA in particular showed excellent precision.
In conclusion, this study has shown that neural networks can be used to
identify bogus news AI generation news created by ChatGPT. The RobertA and BERT
models' excellent performance indicates that these models can play a critical
role in the fight against misinformation.

本研究表明，通过针对 BERT 和 RobertA 模型进行微调，在检测 AI 生成的新闻中取得了最好的效果。Roberta 模型的得分为 98％，精度表现卓越，研究结论表明，神经网络可用于识别 ChatGPT 生成的虚假新闻，并表明这些模型在对抗错误信息方面能够发挥重要作用。