Predicting personality using novel mobile phone-based metrics

Yves Alexandre De Montjoye*, J. Quoidbach, Florent Robic, Alex Pentland

*Autor correspondiente de este trabajo

Producción científica: Capítulo del libroContribución a congreso/conferenciarevisión exhaustiva

229 Citas (Scopus)

Resumen

The present study provides the first evidence that personality can be reliably predicted from standard mobile phone logs. Using a set of novel psychology-informed indicators that can be computed from data available to all carriers, we were able to predict users' personality with a mean accuracy across traits of 42% better than random, reaching up to 61% accuracy on a three-class problem. Given the fast growing number of mobile phone subscription and availability of phone logs to researchers, our new personality indicators open the door to exciting avenues for future research in social sciences. They potentially enable cost-effective, questionnaire-free investigation of personality-related questions at a scale never seen before.

Idioma originalInglés
Título de la publicación alojadaSocial Computing, Behavioral-Cultural Modeling and Prediction - 6th International Conference, SBP 2013, Proceedings
Páginas48-55
Número de páginas8
DOI
EstadoPublicada - 2013
Publicado de forma externa
Evento6th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction, SBP 2013 - Washington, DC, Estados Unidos
Duración: 2 abr 20135 abr 2013

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen7812 LNCS
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia6th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction, SBP 2013
País/TerritorioEstados Unidos
CiudadWashington, DC
Período2/04/135/04/13

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