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Mining large-scale smartphone data for personality studies

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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.

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Notes

  1. http://www.apple.com/iphone/apps-for-iphone/.

  2. http://store.ovi.com/.

  3. http://market.android.com/.

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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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Authors and Affiliations

  1. Idiap Research Institute, Centre du Parc, PO Box 592, Rue Marconi 19, 1920, Martigny, Switzerland

    Gokul Chittaranjan & Daniel Gatica-Perez

  2. École Polytechnique Fédérale de Lausanne (EPFL), 1015, Lausanne, Switzerland

    Gokul Chittaranjan & Daniel Gatica-Perez

  3. Nokia Research Center Lausanne, PSE-C, EPFL, 1015, Lausanne, Switzerland

    Jan Blom

Authors
  1. Gokul Chittaranjan
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  2. Jan Blom
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  3. Daniel Gatica-Perez
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Correspondence to Daniel Gatica-Perez.

Additional information

Based on “Who's who with Big-Five: Analyzing and Classifying Personality Traits with Smartphones” by Gokul Chittaranjan, Jan Blom and Daniel Gatica-Perez which appeared in the Proceedings of the International Symposium on Wearable Computers, San Francisco, California, June 2011. © 2011 IEEE.

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Chittaranjan, G., Blom, J. & Gatica-Perez, D. Mining large-scale smartphone data for personality studies. Pers Ubiquit Comput 17, 433–450 (2013). https://doi.org/10.1007/s00779-011-0490-1

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