Honorable Mention
Recommender systems are increasingly employed by journalistic outlets to deliver personalised news, transforming news curation into a reciprocal yet insufficiently defined process influenced by editors, recommender systems, and individual user actions. To understand the tension in this dynamic and users’ preferences and perceptions of their role in personalised news curation, we conducted a study with UK participants aged 16-34. Building on a preliminary survey and interview study, which revealed a strong desire from participants for increased agency in personalisation, we designed an interactive news recommender provotype (provocative design artefact) which probed the role of agency in news curation with participants (n=16). Findings highlighted a behaviour-intention gap, indicating participants desire for agency yet reluctance to intervene actively in personalisation. Our research offers valuable insights into how users perceive their agency in personalised news curation, underscoring the importance for systems to be designed to support individuals becoming active agents in news personalisation.
doi.org/10.1145/3613904.3642634
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)