推荐质量与消费集中度：来自Netflix的实验证据
Recommendation Quality and the Concentration of Consumption: Experimental Evidence from Netflix
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中文总结 AI 辅助
该研究通过对Netflix850万用户的实验发现，推荐技术改进会提升总消费、用户对推荐的依赖，使消费从超级明星类转向中间尾部类，挑战了推荐系统使消费两极分化的观点，指出中间尾部产品投资回报随算法优化与平台规模扩大而增长。
中文摘要 AI 辅助
我们针对Netflix推荐系统中850万用户开展实验，以探究推荐技术的改进如何影响用户的消费产品集合。改进措施会提升总消费量，增强用户对推荐的依赖，同时将推荐与消费从最热门的“超级明星”类作品扩散至数量更多的中等热门“中间尾部”作品，而对最小众的“长尾”作品影响极小。我们的结果挑战了“推荐系统会使消费两极分化——以中间类作品为代价提升头部与尾部作品消费占比”的观点，并表明随着算法优化与平台规模扩大，对中间尾部产品的投资回报会随之增长。
英文摘要
We study an experiment with 8.5 million users on Netflix's recommender system to measure how improvements in recommendation technology affect the set of products that get consumed. Improvements increase total consumption and users' reliance on recommendations while diffusing recommendations and consumption away from the most popular titles (``superstars") toward a larger number of moderately popular titles (``middle-tail"), with minimal effects on the most niche titles (``long-tail"). Our results challenge the notion that recommender systems polarize consumption -- raising the consumption shares of the head and tail at the expense of the middle -- and suggest that the returns to investing in middle-tail products grow as algorithms improve and platforms scale.
