  This study addresses the critical challenge of detecting DeepFake tweets by
leveraging advanced natural language processing (NLP) techniques to distinguish
between genuine and AI-generated texts. Given the increasing prevalence of
misinformation, our research utilizes the TweepFake dataset to train and
evaluate various machine learning models. The objective is to identify
effective strategies for recognizing DeepFake content, thereby enhancing the
integrity of digital communications. By developing reliable methods for
detecting AI-generated misinformation, this work contributes to a more
trustworthy online information environment.
