The Problem of Emotional Induction Across Online Subject Populations: A Case Study in Guilt and Anger

Understanding online populations is required for successful human-computer interaction (HCI) research, especially among concerns of replicability among human-subjects research. Scholarly works that rely on online populations must use actionable data to support claims of reliability and bias of populations when providing supposedly objective results. In this work, we provide insight into the tribulations of online subject populations’ ability to complete emotional tasks in particular. We explore the populations of the Amazon Mechanical Turk (MTurk) and Prolific platforms and examine the role of emotion induction in a scenario where subjects play a short online game. We discovered unique differences in the two populations’ self-reports of emotion and dropout rates while other quantitative performance results remained significant across both populations, indicating a more nuanced understanding of the fidelity of these populations than previously reported.