Boredom-computer interaction

Abstract

Mobile technology is becoming a loyal companion in our lives. It is used for increasing amounts of time during the day and night, enabling the development of intelligent user interfaces that characterize their users' traits and adapt to them. In this paper, we show how an individual's tendency to experience boredom, i.e. the personal trait called boredom proneness, affects the use of technology -- specifically a smartphone. We develop machine learning models to automatically classify individuals into high/low boredom proneness from their typical daily patterns of smartphone use. We thus propose boredom proneness as a trait with high potential to enable the design of personalized mobile services that are more meaningful to their users.