AIGC虽受偏好冷落，却因高产获同量曝光，算法调节成关键。
Scale over Preference: The Impact of AI-Generated Content on Online Content Ecology
- AIGC以高产量弥补质量劣势，实现与人工内容相当的总曝光。
- 用户更偏爱真人创作内容，但算法推动了AIGC的广泛分发。
- 适合关注平台生态治理与算法公平性的研究者阅读。
人工智能生成内容（AIGC）的迅猛发展正在深刻重塑在线内容生态，亟需对其行为模式与分发机制进行深入分析。本研究基于某中国头部视频平台的纵向数据，涵盖数千万用户，揭示了AIGC与人类生成内容（HGC）在创作与消费行为上的显著差异。研究发现，尽管用户普遍偏好HGC，但AIGC创作者通过高频生产实现了与HGC相当的总体互动量，呈现出‘重规模轻偏好’的动态特征。进一步分析表明，算法分发机制在调和AIGC与用户偏好的冲突中起关键作用。研究呼吁构建对AIGC敏感的分发算法与精准治理框架，以保障在线内容平台的长期健康发展。
原文摘要 · Abstract (English)
The rapid proliferation of Artificial Intelligence-Generated Content (AIGC) is fundamentally restructuring online content ecologies, necessitating a rigorous examination of its behavioral and distributional implications. Leveraging a comprehensive longitudinal dataset comprising tens of millions of users from a leading Chinese video-sharing platform, this study elucidated the distinct creation and consumption behaviors characterizing AIGC versus Human-Generated Content (HGC). We identified a prevalent scale-over-preference dynamic, wherein AIGC creators achieve aggregate engagement comparable to HGC creators through high-volume production, despite a marked consumer preference for HGC. Deeper analysis uncovered the ability of the algorithmic content distribution mechanism in moderating these competing interests regarding AIGC. These findings advocated for the implementation of AIGC-sensitive distribution algorithms and precise governance frameworks to ensure the long-term health of the online content platforms.
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