We developed and validated a scale to measure algorithmic awareness (AMCA-scale)
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This scale contains four underlying dimensions.
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The AMCA-scale was tested for three different online contexts.
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Results revealed strong psychometrics properties for the scale.
Abstract
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.
