Predicting personality using novel mobile phone-based metrics

Yves Alexandre De Montjoye, Jordi Quoidbach, Florent Robic, Alex Pentland

Producció científica: Capítol de llibreContribució a congrés/conferènciaAvaluat per experts

226 Cites (Scopus)

Resum

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 originalAnglès
Títol de la publicacióSocial Computing, Behavioral-Cultural Modeling and Prediction - 6th International Conference, SBP 2013, Proceedings
Pàgines48-55
Nombre de pàgines8
DOIs
Estat de la publicacióPublicada - 2013
Publicat externament
Esdeveniment6th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction, SBP 2013 - Washington, DC, United States
Durada: 2 d’abr. 20135 d’abr. 2013

Sèrie de publicacions

NomLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volum7812 LNCS
ISSN (imprès)0302-9743
ISSN (electrònic)1611-3349

Conferència

Conferència6th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction, SBP 2013
País/TerritoriUnited States
CiutatWashington, DC
Període2/04/135/04/13

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