Study Reveals Scale-over-Preference Dynamic in AI-Generated Content on Video Platforms
A study published on arXiv (2604.01690) analyzing a Chinese video-sharing platform with tens of millions of users found that AI-generated content (AIGC) creators achieve aggregate engagement comparable to human-generated content (HGC) creators through high-volume production, despite consumers preferring HGC. The research identified a 'scale-over-preference' dynamic and highlighted the role of algorithmic content distribution in moderating competing interests. The findings advocate for AIGC-sensitive distribution algorithms and precise governance.
Key facts
- Study uses longitudinal dataset from a leading Chinese video-sharing platform
- Dataset includes tens of millions of users
- AIGC creators achieve comparable engagement through high volume
- Consumers show marked preference for HGC
- Algorithmic distribution moderates competing interests regarding AIGC
- Study advocates for AIGC-sensitive distribution algorithms
- Research published on arXiv with identifier 2604.01690
- Paper title: 'Scale over Preference: The Impact of AI-Generated Content on Online Content Ecology'
Entities
Institutions
- arXiv
Locations
- China