Using Social Sensing to Understand the Links between Sleep, Mood, and Sociability

PASSAT) and 2011 IEEE Third Inernational Conference Social Computing(2011)

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摘要
In recent years, reality mining experiments have provided several novel insights into human social behavior that would not have been possible without the novel use of smart phone sensing. In this work, we leverage the latest reality mining experiment to study social behavior from a public health perspective. In particular, we focus on sleep and mood as they have a considerable public health impact with serious societal and significant financial effects. We endeavor to explore and uncover the associations between sleep, mood and sociability by studying a population of healthy young adults going about their everyday life. We find significant associations between sleep and mood, reiterating observations in the literature. More importantly, we find that individuals with lower overall sociability tend to report poor mood more often, a statistically significant observation. In addition, we also uncover associations between daily sociability and sleep, a previously unreported observation. These results demonstrate the potential of reality mining studies for studying the sociological aspects of significant public health problems. Further, we hope that our work will provide the impetus for larger studies validating some of these observations and ultimately result in behavioral interventions that can improve public health through better social interaction.
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关键词
behavioural sciences computing,data mining,social networking (online),mood behavior,public health perspective,reality mining experiment,sleep behavior,smartphone sensing,sociability behavior,social behavior,social sensing,mood,public health,reality mining,sleep,sociability,social computing,wireless sensing
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