Publication | Open Access
When phones get personal: Predicting Big Five personality traits from application usage
37
Citations
55
References
2020
Year
EngineeringBig FiveSmartphone UsageMobile InteractionBehavior PredictionProblematic Smartphone UseCommunicationPersonality TraitsSocial MediaMobile MarketingData ScienceManagementApplication UsageFactor AnalysisStatisticsCharacter PsychologyUser Behavior ModelingPredictive AnalyticsUser ExperienceUser ProfilingMobile ComputingHuman-computer Interaction
As smartphones are increasingly an integral part of daily life, recent literature suggests a deeper relationship between personality traits and smartphone usage. However, this relationship depends on many complex factors such as geographic location, demographics, or cultural influence, just to name a few. These factors provide crucial knowledge for e.g. usage support, recommendations, marketing, general usage improvements. We use six months of application usage data from 739 Android smartphone user together with the IPIP 50-item Big Five personality traits questionnaire. As our main contribution, we show that even category-level aggregated application usage can predict Big Five traits at up to 86%–96% prediction fit in our sample. Our results show the effect of personality traits on application usage (mean error improvement on random guess 17.0%). We also identify which application usage data best describe the Big Five personality traits. Our work enables future personality-driven research, and shows that when studying personality, application categories can provide sufficient predictions in general traits.
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