I went straight to defining what 'trending' even means, which I think saved me.
Start by clarifying the goal and scope of 'trending topics' for a News app, then propose a data-driven design that balances real-time signals with personalization and editorial oversight. Structure your answer around user needs, algorithmic approach, and success metrics, showing how you'd iterate based on feedback.
Pro tip: Emphasize the importance of defining 'trending' precisely—e.g., velocity of mentions, diversity of sources, and decay over time—and discuss how you'd guard against manipulation and filter bubbles, which shows product maturity.
Ask clarifying questions to understand the target users, business objectives (e.g., engagement, retention), and constraints (e.g., real-time vs. daily updates, global vs. local).
Specify what makes a topic trending (e.g., sudden spike in mentions, cross-source coverage) and outline data sources such as article volume, social shares, search queries, and user interactions.
Propose a ranking system that combines recency, velocity, diversity, and personalization, while incorporating safeguards against spam and misinformation.
Choose metrics like click-through rate, time spent, and topic diversity, and describe how you'd A/B test and refine the feature based on user feedback and data.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.