Online media platforms are increasingly using algorithms to select and present relevant information to their audiences. This highlights the importance of exploring whether people are aware of algorithmic content recommendations. Although some studies have already investigated algorithmic awareness, no standardized instrument has been developed yet to assess this construct. In this study, we therefore developed and validated the Algorithmic Media Content Awareness Scale (AMCA-scale). This scale contains four underlying dimensions: 1) users’ awareness of content filtering, 2) users’ awareness of automated decision-making, 3) users’ awareness of human-algorithm interplay, and 4) users’ awareness of ethical considerations. In validating the scale, results revealed strong psychometrics properties. The AMCA-scale was also successfully tested for three different online platforms: Facebook, YouTube, and Netflix, showing its robustness over different environments. Based on these findings, we conclude that the AMCA-scale offers scholars a valid, reliable and robust tool to measure algorithmic awareness.

在线媒体平台越来越多地使用算法来选择相关信息并将其呈现给其受众。这凸显了探索人们是否了解算法内容推荐的重要性。尽管一些研究已经研究了算法意识，尚未开发标准化工具来评估此结构。因此，在这项研究中，我们开发并验证了算法媒体内容意识量表（AMCA量表）。该量表包含四个基本维度：1）用户对内容过滤的意识； 2）用户对自动决策的意识； 3）用户对人与算法的相互作用的意识；以及4）用户对道德考量的意识。在验证量表时，结果显示出强大的心理计量学特性。AMCA量表还成功在三个不同的在线平台上进行了测试：Facebook，YouTube和Netflix，显示了其在不同环境下的稳健性。基于这些发现，我们得出结论，AMCA量表为学者提供了一种有效，可靠和强大的工具来衡量算法意识。