Design a personalized news ranking system.

Focus on the key components of a personalized news ranking system, including user data collection, content categorization, and ranking algorithms. Discuss how you would gather user preferences and behavior through explicit feedback (likes, follows) and implicit signals (reading time, shares). Consider different ranking algorithms, such as collaborative filtering or content-based filtering, and explain how you would balance relevance and diversity in the news feed. Address potential challenges like bias in the data and ensuring the system adapts to changing user interests over time. Finally, think about how you would measure the success of the system through user engagement metrics.