My PhD project explores media bias on digital platforms, focusing on detection, the impact of news recommendation algorithms, and mitigation strategies. Automated detection of media bias is essential but challenging due to the scarcity of high-quality labeled datasets. Personalized news recommendation systems, while designed to cater to user preferences, may inadvertently amplify bias by creating information bubbles. This project investigates the role of these algorithms in the spread of media bias and their long-term effects on news consumption. Additionally, it explores automatic sentence rewriting methods to enhance objectivity in news reporting and reduce biased content. The goal is to improve the quality and fairness of news consumption, contributing to a more informed public discourse.