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In this rapidly digitizing world, it is becoming ever more important to understand people's online behaviors in both scientific and consumer research settings. The current work tests the feasibility of inferring personality traits from mouse movement patterns as a cost‐effective means of measuring individual characteristics.

Mouse movement features (i.e., pauses, fixations, speed, and clicks) were collected while participants (N = 791) completed an online image choice task. We compare the results of standard univariate and three forms of multivariate partial least squares (PLS) analyses predicting Big Five traits from mouse movements. We also examine whether mouse movements can predict a proposed measure of task attentiveness (atypical responding), and how these might be related to personality traits.

Each of the PLS analyses showed significant associations between a linear …