Learning to Pay Attention: Unsupervised Modeling of Attentive and Inattentive Respondents in Survey Data

Researchers developed an unsupervised machine learning framework using autoencoders and probabilistic models to detect inattentive survey respondents without traditional attention checks. The study found that survey structure is more important than model complexity for detection effectiveness, with well-designed instruments enabling reliable identification of low-quality responses.