ABSTRACT

With the increasing implementation of algorithms across various news platforms, understanding news consumers’ subjective perceptions of algorithmic-based news recommender systems has become critical. A between-subjects experiment (News Recommender System type: content-based filtering vs. collaborative filtering vs. human editorial choice-based recommender system) with 161 participants revealed that participants tended to trust the collaborative filtering system and perceive news recommended by the system to be more credible and less biased compared to editorial choices-based or content-based recommender systems – due to the triggering of the homophily heuristic – even though the three systems recommended the same set of news. Implications were discussed.

摘要

随着算法在各种新闻平台上的应用越来越多，了解新闻消费者对基于算法的新闻推荐系统的主观看法变得至关重要。一项由 161 名参与者参与的受试者间实验（新闻推荐系统类型：基于内容的过滤与协同过滤与基于人工编辑选择的推荐系统）显示，参与者倾向于信任协同过滤系统，并认为系统推荐的新闻与基于编辑选择或基于内容的推荐系统相比，由于同质启发式的触发，即使这三个系统推荐了同一组新闻，它也更可信且更少偏见。讨论了影响。