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Automatically Detecting Task-Unrelated Thoughts During Conversations Using Keystroke Analysis

User modeling and user-adapted interaction(2022)

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摘要
Task-unrelated thought (TUT), commonly referred to as mind wandering, is a mental state where a person’s attention moves away from the task-at-hand. This state is extremely common, yet not much is known about how to measure it, especially during dyadic interactions. We thus built a model to detect when a person experiences TUTs while talking to another person through a computer-mediated conversation, using their keystroke patterns. The best model was able to differentiate between task-unrelated thoughts and task-related thoughts with a kappa of 0.363, using features extracted from a 15 second window. We also present a feature analysis to provide additional insights into how various typing behaviors can be linked to our ongoing mental states.
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关键词
Task-unrelated thought,Keystrokes,Machine learning,Affective computing,Mind wandering
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