This paper presents a web application designed to study the impact of explainable AI (XAI) and XAI interactivity on fake news detection. The system enables a controlled user study with a 2×2 design, varying XAI interactivity (high vs. low) and explanation type (counterfactual vs. feature importance). High interactivity conditions utilize an LLM-based chatbot for dynamic explanations, while low interactivity conditions provide fixed, predetermined explanations. The demonstration highlights how AI explanations influence user trust, reliance, and learning in news verification tasks. The web application’s video showcasing the main features is available at: https://drive.google.com/file/d/1_U5wUoHMrUEHFSXrna90LpWjnUbv9eJn/view?usp=sharing