MoodScope: Building a Mood Sensor from Smartphone Usage Patterns

dc.contributor.advisorZhong, Linen_US
dc.contributor.committeeMemberSabharwal, Ashutoshen_US
dc.contributor.committeeMemberSubramanian, Devikaen_US
dc.creatorLi Kam Wa, Roberten_US
dc.date.accessioned2012-09-06T04:05:15Zen_US
dc.date.accessioned2012-09-06T04:05:18Zen_US
dc.date.available2012-09-06T04:05:15Zen_US
dc.date.available2012-09-06T04:05:18Zen_US
dc.date.created2012-05en_US
dc.date.issued2012-09-05en_US
dc.date.submittedMay 2012en_US
dc.date.updated2012-09-06T04:05:18Zen_US
dc.description.abstractMoodScope is a first-of-its-kind smartphone software system that learns the mood of its user based on how the smartphone is used. While commonly available sensors on smartphones measure physical properties, MoodScope is a sensor that measures an important mental state of the user and brings mood as an important context into context-aware computing. We design MoodScope using a formative study with 32 participants and collect mood journals and usage data from them over two months. Through the study, we find that by analyzing communication history and application usage patterns, we can statistically infer a user’s daily mood average with 93% accuracy after a two-month training period. To a lesser extent, we can also estimate Sudden Mood Change events with reasonable accuracy (74%). Motivated by these results, we build a service, MoodScope, which analyzes usage history to act as a sensor of the user’s mood. We provide a MoodScope API for developers to use our system to create mood-enabled applications and create and deploy sample applications.en_US
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationLi Kam Wa, Robert. "MoodScope: Building a Mood Sensor from Smartphone Usage Patterns." (2012) Master’s Thesis, Rice University. <a href="https://hdl.handle.net/1911/64654">https://hdl.handle.net/1911/64654</a>.en_US
dc.identifier.slug123456789/ETD-2012-05-114en_US
dc.identifier.urihttps://hdl.handle.net/1911/64654en_US
dc.language.isoengen_US
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.en_US
dc.subjectMobile computingen_US
dc.subjectAffective computingen_US
dc.titleMoodScope: Building a Mood Sensor from Smartphone Usage Patternsen_US
dc.typeThesisen_US
dc.type.materialTexten_US
thesis.degree.departmentElectrical and Computer Engineeringen_US
thesis.degree.disciplineEngineeringen_US
thesis.degree.grantorRice Universityen_US
thesis.degree.levelMastersen_US
thesis.degree.nameMaster of Scienceen_US
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