Cooperation with a robotic assistant
CHI '02 Extended Abstracts on Human Factors in Computing Systems
Designing social presence of social actors in human computer interaction
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
NEmESys: neural emotion eliciting system
CHI '05 Extended Abstracts on Human Factors in Computing Systems
Personality and self reported mobile phone use
Computers in Human Behavior
Measuring personality from keyboard and mouse use
ECCE '08 Proceedings of the 15th European conference on Cognitive ergonomics: the ergonomics of cool interaction
Towards user psychological profile
Proceedings of the VIII Brazilian Symposium on Human Factors in Computing Systems
Combating obesity trends in teenagers through persuasive mobile technology
ACM SIGACCESS Accessibility and Computing
Automatic recognition of personality in conversation
NAACL-Short '06 Proceedings of the Human Language Technology Conference of the NAACL, Companion Volume: Short Papers
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
Predicting personality using novel mobile phone-based metrics
SBP'13 Proceedings of the 6th international conference on Social Computing, Behavioral-Cultural Modeling and Prediction
Influence of personality on satisfaction with mobile phone services
ACM Transactions on Computer-Human Interaction (TOCHI)
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Knowing the users' personality can be a strategic advantage for the design of adaptive and personalized user interfaces. In this paper, we present the results of a first trial conducted with the aim of inferring people's personality traits based on their mobile phone call behavior. Initial findings corroborate the efficacy of using call detail records (CDR) and Social Network Analysis (SNA) of the call graph to infer the Big Five personality factors. On-going work includes a large-scale study that shall refine the accuracy of the models with a reduced margin of error.