SensorApp: A Move Speaks Louder Than Words: Personality recognition using a dataset obtained from sensors and mobile device usage habits

Personality is a set of traits that describe people, such as emotions and behavioral patterns. Therefore, it is easy to believe that these patterns influence the way in which people interact with mobile devices. Since they are so widely used in everyday life and considering that most people have one of them, it becomes fundamental to create a dataset based on mobile device usage habits. The purpose of this is to recognize the personality of the users based on how they use their data. This paper presents the methodology in which the data was collected, as well as the neural networks used to perform preliminary personality recognition tests, using different metrics, getting promising personality prediction data with the use of ANN and MLP networks and the data obtained from mobile devices.

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Publication Details

Journal
International Journal of Combinatorial Optimization Problems and Informatics.
Published
2025-10-12
DOI
https://doi.org/10.61467/2007.1558.2025.v16i4.1018
Primary Topic
Personality Traits and Psychology
Type
article
Field-Weighted Citation Impact
0.00
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article

SensorApp: A Move Speaks Louder Than Words: Personality recognition using a dataset obtained from sensors and mobile device usage habits

Ramón Zataraín Cabada, Hugo Jair Escalante, María Lucía Barrón Estrada, Néstor Leyva López
International Journal of Combinatorial Optimization Problems and Informatics.
Personality Traits and Psychology
article

SensorApp: A Move Speaks Louder Than Words: Personality recognition using a dataset obtained from sensors and mobile device usage habits

Ramón Zataraín Cabada, Hugo Jair Escalante, María Lucía Barrón Estrada, Néstor Leyva López
article en

Abstract

Personality is a set of traits that describe people, such as emotions and behavioral patterns. Therefore, it is easy to believe that these patterns influence the way in which people interact with mobile devices. Since they are so widely used in everyday life and considering that most people have one of them, it becomes fundamental to create a dataset based on mobile device usage habits. The purpose of this is to recognize the personality of the users based on how they use their data. This paper presents the methodology in which the data was collected, as well as the neural networks used to perform preliminary personality recognition tests, using different metrics, getting promising personality prediction data with the use of ANN and MLP networks and the data obtained from mobile devices.

International Journal of Combinatorial Optimization Problems and Informatics.Vol. 16(4)
National Institute of Astrophysics, Optics and Electronics (MX), Instituto Tecnológico de Culiacán (MX), Tecnológico Nacional de México (MX), Centro Nacional de Investigación y Desarrollo Tecnológico (MX)
Openalex Percentile: Top 60%
Personality Traits and Psychology
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