Using Facial Expressions to Predict Process Mining Task Performance

Process mining analysis is a complex task that presents significant challenges to human analysts. To aid along this process, it is essential to identify difficulties as they occur. This study takes an initial step in this direction, by predicting the quality of task performance based on analysts’ facial expressions while they are engaged in a process mining task. Data were collected using participants’ webcams and the iMotions™ cloud application while they performed a process mining task. The data were then utilized to train and evaluate several machine learning classifiers, which classified participants based on the grade given to their task outcome. Our results show the high performance of these classifiers in predicting participants’ success based on facial expressions. We further showed that the chosen outcome classifier could accurately classify additional participants, demonstrating its generalizability. Notably, the classifier was able to predict participants’ success within a very short time frame. These findings could pave the way for developing a near-real-time support system to detect when analysts engaged in process mining may benefit from assistance.