Employing think-aloud protocol to connect user emotions and mouse movements

This paper describes unobtrusive method for user confusion detection by monitoring mouse movements. A special computer game was designed to collect mouse logs. Think-aloud protocol was used in order to identify the states of confusion. Features extracted from mouse movement´s logs were used in training dataset. Support Vector Machines, Logistic Regression, C4.5 and Random Forest were used to build classification models. Model generated by Random Forest yield to best classification results with f-score 0.938.