The Relationships Between Behavioral Patterns and Emotions in Daily Life
Emotions have been recognized from physiological and behavioral responses, however, in daily life these methods are less practical due to the measurement burden. This study was to minimize the measurement burden by using smartphones and to determine the behavioral patterns relevant to daily emotions through the global positioning system (GPS) locations. Seven participants (5 males) were asked to carry their smartphones and evaluate subjective emotions for six weeks. The participants’ GPS locations were measured with their smartphones and then analyzed to determine their behavioral patterns. The emotions were categorized into valence and arousal dimensions, and the behavioral patterns were tested by the Kruskal-Wallis method. As a result, the valence dimension implied significant behavioral patterns such as location variance (p = .006), number of cluster (p = .015), and entropy (p = .044). The arousal dimension implied significant behavioral patterns such as location variance (p = .003), circadian movement (p = .008), and transition time (p = .016). These behavioral patterns are expected to be useful in recognizing emotions in daily life.
KeywordsBehavioral patterns Emotion Global positioning system (GPS) Smartphone
This work was supported by the Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIT) (No.2015-0-00312, The development of technology for social life logging based on analyzing social emotion and intelligence of convergence contents).
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