Fake Tweet

Fake tweet detection research focuses on automatically identifying AI-generated or deliberately misleading tweets, aiming to improve the trustworthiness of online information. Current approaches leverage natural language processing (NLP) techniques, often employing machine learning models like Random Forests and deep learning architectures such as LSTMs and transformer-based models (e.g., DeBERTa), sometimes incorporating multimodal data like images and replies for enhanced accuracy. These efforts are significant because they address the widespread problem of misinformation on social media, with potential applications in combating the spread of false narratives and improving public trust in online information.