The Cold Start Problem: How to Start and Scale Network Effects

by Andrew Chen

On TikTok, the For You feed reflects preferences unique to each user. The system recommends content by ranking videos based on a combination of factors—starting from interests you express as a new user and adjusting for things you indicate you’re not interested in, too—to form your personalized For You feed. Recommendations are based on a number of factors, including things like: User interactions such as the videos you like or share, accounts you follow, comments you post, and content you create. Video information, which might include details like captions, sounds, and hashtags. Device and account settings like your language preference, country setting, and device type. These factors are included to make sure the system is optimized for performance, but they receive lower weight in the recommendation system relative to other data points we measure since users don’t actively express these as preferences.