Personal and Ubiquitous Computing

, Volume 17, Issue 3, pp 433–450 | Cite as

Mining large-scale smartphone data for personality studies

  • Gokul Chittaranjan
  • Jan Blom
  • Daniel Gatica-Perez
Original Article

Abstract

In this paper, we investigate the relationship between automatically extracted behavioral characteristics derived from rich smartphone data and self-reported Big-Five personality traits (extraversion, agreeableness, conscientiousness, emotional stability and openness to experience). Our data stem from smartphones of 117 Nokia N95 smartphone users, collected over a continuous period of 17 months in Switzerland. From the analysis, we show that several aggregated features obtained from smartphone usage data can be indicators of the Big-Five traits. Next, we describe a machine learning method to detect the personality trait of a user based on smartphone usage. Finally, we study the benefits of using gender-specific models for this task. Apart from a psychological viewpoint, this study facilitates further research on the automated classification and usage of personality traits for personalizing services on smartphones.

Keywords

Smartphones Big-Five Personality Lausanne data collection campaign 

Notes

Acknowledgments

This work was funded by the SNSF project “Sensing and Analyzing Organizational Nonverbal Behavior" (SONVB) and by Nokia Research Center (NRC) Lausanne. We thank Juha K. Laurila (NRC) and Trinh-Minh-Tri Do (Idiap) for valuable discussions.

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Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  • Gokul Chittaranjan
    • 1
    • 2
  • Jan Blom
    • 3
  • Daniel Gatica-Perez
    • 1
    • 2
  1. 1.Idiap Research InstituteCentre du ParcMartignySwitzerland
  2. 2.École Polytechnique Fédérale de Lausanne (EPFL)LausanneSwitzerland
  3. 3.Nokia Research Center LausannePSE-C, EPFLLausanneSwitzerland

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