The meteoric rise of short-form video platforms like YouTube Shorts, Facebook Reels, and TikTok has revolutionized how people consume digital content, drawing billions of daily users worldwide. These platforms rely on advanced recommendation systems to keep users engaged by offering personalized video suggestions. However, ranking short and long-form videos together presents a significant challenge: duration bias.

Unlike traditional recommendation systems that rely on explicit user actions like likes or shares, video platforms primarily utilize watch time and completion rates as their core engagement metric. This shift stems from the limited availability of direct user feedback, making watch metrics a practical proxy for gauging interest. However, this approach introduces an inherent bias where shorter videos are favored over equally engaging longer content because they naturally achieve higher completion rates. For instance, if a user watches 15 seconds of a 30-second video (50% completion) but spends 30 seconds on a 2-minute video (25% completion), the recommender system may interpret the first interaction as more engaging and favor the shorter video, even though both could have been equally interesting to the user. This systematic skew toward shorter content impacts the entire ecosystem, affecting user satisfaction, limiting content diversity, and discouraging creators from producing longer videos.

https://dzone.com/articles/duration-bias-in-video-recommendations