MoodScope: Building a mood sensor from smartphone usage patterns

Robert Likamwa, Yunxin Liu, Nicholas D. Lane, Lin Zhong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

110 Scopus citations

Abstract

We report a first-of-its-kind smartphone software system, MoodScope, which infers the mood of its user based on how the smartphone is used. Compared to smartphone sensors that measure acceleration, light, and other physical properties, MoodScope is a "sensor" that measures the mental state of the user and provides mood as an important input to context-aware computing. We run a formative statistical mood study with smartphone-logged data collected from 32 participants 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 an initial accuracy of 66%, which gradually improves to an accuracy of 93% after a two-month personalized training period. 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. We further create and deploy a mood-sharing social application.

Original languageEnglish (US)
Title of host publicationMobiSys 2013 - Proceedings of the 11th Annual International Conference on Mobile Systems, Applications, and Services
Pages389-401
Number of pages13
DOIs
StatePublished - Aug 12 2013
Externally publishedYes
Event11th Annual International Conference on Mobile Systems, Applications, and Services, MobiSys 2013 - Taipei, Taiwan, Province of China
Duration: Jun 25 2013Jun 28 2013

Publication series

NameMobiSys 2013 - Proceedings of the 11th Annual International Conference on Mobile Systems, Applications, and Services

Other

Other11th Annual International Conference on Mobile Systems, Applications, and Services, MobiSys 2013
CountryTaiwan, Province of China
CityTaipei
Period6/25/136/28/13

Keywords

  • Affective computing
  • Machine learning
  • Mobile systems
  • Mood
  • Smartphone usage

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications

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  • Cite this

    Likamwa, R., Liu, Y., Lane, N. D., & Zhong, L. (2013). MoodScope: Building a mood sensor from smartphone usage patterns. In MobiSys 2013 - Proceedings of the 11th Annual International Conference on Mobile Systems, Applications, and Services (pp. 389-401). (MobiSys 2013 - Proceedings of the 11th Annual International Conference on Mobile Systems, Applications, and Services). https://doi.org/10.1145/2462456.2464449