When phones get personal : predicting big five personality traits from application usage
Ella Peltonen,Parsa Sharmila,Kennedy Opoku Asare,Aku Visuri,Eemil Lagerspetz,Denzil Ferreira +5 more
TLDR
It is shown that even category-level aggregated application usage can predict Big Five traits at up to 86%–96% prediction fit in the authors' sample, and that when studying personality, application categories can provide sufficient predictions in general traits.About:
This article is published in Pervasive and Mobile Computing.The article was published on 2020-11-01 and is currently open access. It has received 17 citations till now. The article focuses on the topics: Personality & Big Five personality traits.read more
Citations
More filters
Journal ArticleDOI
Predicting Depression From Smartphone Behavioral Markers Using Machine Learning Methods, Hyperparameter Optimization, and Feature Importance Analysis: Exploratory Study
Kennedy Opoku Asare,Yannik Terhorst,Julio Vega,Ella Peltonen,Eemil Lagerspetz,Denzil Ferreira +5 more
TL;DR: In this paper, the authors explored the relationship between the behavioral features and depression using correlation and bivariate linear mixed models (LMMs) and leveraged 5 supervised machine learning (ML) algorithms with hyperparameter optimization, nested cross-validation, and imbalanced data handling to predict depression.
Journal ArticleDOI
Smartphone App Usage Analysis: Datasets, Methods, and Applications
TL;DR: This survey summarizes advanced technologies and key patterns in smartphone app usage behaviors, all of which have significant implications for all relevant stakeholders, including academia and industry, in this survey.
Journal ArticleDOI
Show me your smartphone… and then I will show you your brain structure and brain function
Journal ArticleDOI
Mood ratings and digital biomarkers from smartphone and wearable data differentiates and predicts depression status: A longitudinal data analysis
Kennedy Opoku Asare,Isaac Moshe,Yannik Terhorst,Julio Vega,Simo Hosio,Harald Baumeister,Laura Pulkki-Råback,Denzil Ferreira +7 more
TL;DR: In this article , the authors used wearable sensors and self-reported mood scores and passive smartphone and wearable sensor data to classify people as depressed or non-depressed, and found statistically significant differences in GPS mobility, phone usage, sleep, physical activity and mood between depressed and nondepressed groups.
Journal ArticleDOI
Putting human behavior predictability in context
Wanyi Zhang,Qiang Shen,Stefano Teso,Bruno Lepri,Andrea Passerini,Ivano Bison,Fausto Giunchiglia,Fausto Giunchiglia +7 more
TL;DR: In this article, the authors investigate the role played by four contextual dimensions (or modalities) on the predictability of individuals' behaviors, using a month of collected mobile phone sensor readings and self-reported annotations about these contextual modalities from more than two hundred study participants.
References
More filters
The Big Five Trait taxonomy: History, measurement, and theoretical perspectives.
Oliver P. John,Sanjay Srivastava +1 more
TL;DR: The Big Five taxonomy as discussed by the authors is a taxonomy of personality dimensions derived from analyses of the natural language terms people use to describe themselves 3 and others, and it has been used for personality assessment.
Journal ArticleDOI
The development of markers for the big-five factor structure
TL;DR: In this paper, a set of 100 unipolar terms for personality traits was developed and compared with previously developed ones based on far larger sets of trait adjectives, as well as with the scales from the NEO and Hogan personality inventories.
Journal ArticleDOI
The Structure of Phenotypic Personality Traits
TL;DR: This personal historical article traces the development of the Big-Five factor structure, whose growing acceptance by personality researchers has profoundly influenced the scientific study of individual differences.
Journal ArticleDOI
The international personality item pool and the future of public-domain personality measures ☆
Lewis R. Goldberg,John A. Johnson,Herbert W. Eber,Robert Hogan,Michael C. Ashton,C. Robert Cloninger,Harrison G. Gough +6 more
TL;DR: The International Personality Item Pool (IPIP) as mentioned in this paper has been used as a prototype for public-domain personality measures, focusing on the International personality item pool, which has been widely used for personality measurement.