Mouse movements reflect personality traits and task attentiveness in online experiments

In this rapidly digitizing world, it is becoming ever more important to understand people’s online behaviors in both scientific and consumer research settings. A cost-effective way to gain a deeper understanding of these behaviors is to examine mouse movement patterns. This research explores the feasibility of inferring personality traits from these mouse movement features (i.e., pauses, fixations, cursor speed, clicks) on a simple image choice task. We compare the results of standard univariate (OLS regression, bivariate correlations) and three forms of multivariate partial least squares (PLS) analyses. This work also examines whether mouse movements can predict task attentiveness, and how these might be related to personality traits. Results of the PLS analyses showed significant associations between a linear combination of personality traits (high Conscientiousness, Agreeableness, and Openness, and low Neuroticism) and several mouse movements associated with slower, more deliberate responding (less unnecessary clicks, more fixations). Additionally, several click-related mouse features were associated with attentiveness to the task. Importantly, as the image choice task itself is not intended to assess personality in any way, our results validate the feasibility of using mouse movements to infer internal traits across experimental contexts, particularly when examined using multivariate analyses and a multiverse approach.