Fake News Detection Using Logistic Regression: A Machine Learning Approach to Fighting Misinformation

In the digital age, information spreads at an unprecedented speed. Social media platforms, online news portals, and messaging applications allow news to travel across the globe within seconds. While this instant connectivity has transformed communication positively, it has also created a serious global challenge — the rapid spread of fake news. False or misleading information can influence public opinion, create unnecessary panic, damage reputations, and even impact political and economic stability. Because millions of articles, posts, and headlines are generated daily, manually verifying each piece of information is nearly impossible. This is where machine learning provides a powerful and scalable solution. Fake news detection can be viewed as a binary classification problem in which a machine learning model must determine whether a news article is real or fake. Among the many algorithms available for classification tasks, Logistic Regression remains one of the most reliable and inter