Happiness recognition from smartphone usage data considering users’ estimated personality traits

Abstract

The daily and routine interactions of people with their smartphones in various situations make these devices valuable data sources to understand user behaviors. Passive users’ emotion recognition is one of the most essential user modeling areas and has been studied for various purposes so far. Psychological studies, on the other hand, show that the personality of users can influence their behavior when they experience different emotions. Individuals with varying types of personality exhibit different reactions in the same emotional situation. It is concluded that if we consider the user's personality in passive recognition of his/her emotion, the emotion can be identified more accurately. However, researchers have not paid enough attention to the users’ personality traits when identifying the users’ emotions based on their interaction with cell phones. In the present study, we strive to address this research gap. Among the various emotions, our focus is on happiness recognition. In our proposed method, the user's personality traits are first estimated based on his/her interactions with the smartphone. Then the estimated personality of the user, along with the data of his/her interactions with the smartphone, is taken into account to recognize his/her happiness. Evaluations showed that taking into account the users’ personality traits reduces the happiness recognition error. © 2021 Elsevier B.V.