Implementing BERT and fine-tuned RobertA to detect AI generated news by
  ChatGPT
Zecong Wang Jiaxi Cheng Chen Cui Chenhao Yu
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.