AI-Based Fake News Detection Using Machine Learning And Explainable AI

Authors: Ms. Sayana Garudik, Ms. Pari Purohit, Mrs. Neeku Sahu, Mrs. Shruti Mehta

Abstract: Fake news has become a serious issue in the digital world, spreading misinformation rapidly through social media and online platforms. Detecting fake news manually is difficult due to the large volume of data. In this research, we propose an AI-based fake news detection system using machine learning (ML) models. The dataset is preprocessed and multiple ML algorithms such as Logistic Regression (LR), Random Forest (RF), Support Vector Machine (SVM), Naive Bayes (NB), K-Nearest Neighbors (KNN), and XGBoost (XGB) are applied. Feature selection techniques are used to improve accuracy, and Explainable AI tools like SHAP and LIME are used to interpret model predictions. The best-performing model is deployed for real-time fake news detection through web-based applications.

DOI: http://doi.org/10.5281/zenodo.20201805