Abstract

News recommender systems provide a technological architecture that helps shaping public discourse. Following a normative approach to news recommender system design, we test utility and external effects of a diversity-aware news recommender algorithm. In an experimental study using a custom-built news app, we show that diversity-optimized recommendations (1) perform similar to methods optimizing for user preferences regarding user utility, (2) that diverse news recommendations are related to a higher tolerance for opposing views, especially for politically conservative users, and (3) that diverse news recommender systems may nudge users towards preferring news with differing or even opposing views. We conclude that diverse news recommendations can have a depolarizing capacity for democratic societies.

摘要

新闻推荐系统提供了一种有助于塑造公共话语的技术架构。按照新闻推荐系统设计的规范方法，我们测试了多样性感知新闻推荐算法的效用和外部效果。在使用定制新闻应用程序的实验研究中，我们表明多样性优化的推荐 (1) 执行类似于针对用户效用的用户偏好优化的方法，(2) 多样化的新闻推荐与对相反观点的更高容忍度相关，特别是对于政治上保守的用户，以及（3）多样化的新闻推荐系统可能会促使用户偏爱具有不同甚至相反观点的新闻。我们的结论是，多样化的新闻推荐对民主社会具有去极化的能力。