Modeling the dynamics of observational behaviors base on observers' personality traits using hidden Markov Models

Previous studies indicated that how people look at others' faces depends on observers' characteristics. A vast majority of these studies used aggregated data, treating gaze data in a static manner and often neglected dynamics of observational behaviors. The present study, on the other hand, examined the relationship between observers' personality traits and observational behaviors (i.e., which areas of face were looked at) using time-series eye movement data. In particular, we collected gaze data using a smile judgments task, asking participants to judge whether smiley faces were genuine or not. Observational behav-iors were analyzed using a hidden Markov model. The results showed that participants with different patterns of personality traits exhibited different transition patterns. In addition, there were also significant interactions between personality traits and the number of hidden states each participant had. Furthermore, there were significant relationships between participants' person-ality traits and the result of judgments.