Using Machine Learning To Detect Fake News

22 May
Posted on Author

Authors: Reshoo Devi, Ashish Kumar, Baiju Kumar Yadav

Abstract: Fake news detection has become an urgent priority due to the widespread misinformation on digital platforms. A machine learning-based system is proposed in this research to classify news articles as real or fake using Natural Language Processing (NLP). The study utilizes TF-IDF vectorization and supervised learning algorithms like Logistic Regression, Naive Bayes, Random Forest, and Decision Tree to identify the most effective model for journalists, fact-checkers, and social media platforms. Logistic regression was discovered to be the most accurate model with 92% accuracy, demonstrating the power of machine learning in combating digital misinformation.

DOI: http://doi.org/10.5281/zenodo.20338924