Please, tell me about yourself: automatic personality assessment using short self-presentations
ICMI '11 Proceedings of the 13th international conference on multimodal interfaces
Friends don't lie: inferring personality traits from social network structure
Proceedings of the 2012 ACM Conference on Ubiquitous Computing
Mining large-scale smartphone data for personality studies
Personal and Ubiquitous Computing
Influence of personality on satisfaction with mobile phone services
ACM Transactions on Computer-Human Interaction (TOCHI)
MoodScope: building a mood sensor from smartphone usage patterns
Proceeding of the 11th annual international conference on Mobile systems, applications, and services
User demographics prediction based on mobile data
Pervasive and Mobile Computing
Visual analysis of social networks in space and time using smartphone logs
Pervasive and Mobile Computing
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In this paper, we investigate the relationship between behavioral characteristics derived from rich smart phone data and self-reported personality traits. Our data stems from smart phones of a set of 83 individuals collected over a continuous period of 8 months. From the analysis, we show that aggregated features obtained from smart phone usage data can be indicators of the Big-Five personality traits. Additionally, we develop an automatic method to infer the personality type of a user based on cell phone usage using supervised learning. We show that our method performs significantly above chance and up to 75.9% accuracy. To our knowledge, this constitutes the first study on the analysis and classification of personality traits using smartphone data.