Predicting personality using novel mobile phone-based metrics

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

*Corresponding author for this work

Research output: Book chapterConference contributionpeer-review

229 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationSocial Computing, Behavioral-Cultural Modeling and Prediction - 6th International Conference, SBP 2013, Proceedings
Pages48-55
Number of pages8
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event6th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction, SBP 2013 - Washington, DC, United States
Duration: 2 Apr 20135 Apr 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7812 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference6th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction, SBP 2013
Country/TerritoryUnited States
CityWashington, DC
Period2/04/135/04/13

Keywords

  • Big Data
  • Big Five Personality prediction
  • CDR
  • Carrier's log
  • Personality prediction

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