Work

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

Year: 2025

Type: article

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.

Source: International Journal of Combinatorial Optimization Problems and Informatics.

DOI: 10.61467/2007.1558.2025.v16i4.1018

Authors: Néstor Leyva López, Ramón Zatarain Cabada, Hugo Jair Escalante Balderas, María Lucía Barrón Estrada

Institutions: Tecnológico Nacional de México, National Institute of Astrophysics, Optics and Electronics

Language: English

Topic: Context-Aware Activity Recognition Systems

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

OpenAlex ID: W4415089263

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