Articles producció científica> Filologies Romàniques

Machine Learning Methods for Automatic Gender Detection

  • Identification data

    Identifier: imarina:9262211
    Handle: https://hdl.handle.net/20.500.11797/imarina9262211
    Authors:
    Morales Sanchez, DamianMoreno, AntonioJimenez Lopez, M. Dolores
    Abstract:
    Automatic gender detection has attracted the attention of many research fields such as forensic linguistics or marketing. Within these areas, gender detection has been approached as a classification problem and, for this reason, supervised Machine Learning algorithms such as Naive Bayes, Logistic Regression and Support Vector Machines, among others, have been employed. The latter algorithm has exhibited a better performance on gender detection. In recent years, with the development of Deep Learning methods, various neural networks structures such as Convolutional Neural Networks have been designed for gender detection. However, Deep Learning methods have led to a loss in the interpretability of the models. In this article, we review the AI techniques applied on gender detection.

  • Others:

    Author, as appears in the article.: Morales Sanchez, Damian; Moreno, Antonio; Jimenez Lopez, M. Dolores;
    Department: Enginyeria Informàtica i Matemàtiques Filologies Romàniques
    URV's Author/s: Jiménez López, María Dolores / Moreno Ribas, Antonio
    Keywords: Machine learning Gender detection Author profiling
    Abstract: Automatic gender detection has attracted the attention of many research fields such as forensic linguistics or marketing. Within these areas, gender detection has been approached as a classification problem and, for this reason, supervised Machine Learning algorithms such as Naive Bayes, Logistic Regression and Support Vector Machines, among others, have been employed. The latter algorithm has exhibited a better performance on gender detection. In recent years, with the development of Deep Learning methods, various neural networks structures such as Convolutional Neural Networks have been designed for gender detection. However, Deep Learning methods have led to a loss in the interpretability of the models. In this article, we review the AI techniques applied on gender detection.
    Thematic Areas: Interdisciplinar Engenharias iv Engenharias iii Computer science, interdisciplinary applications Computer science, artificial intelligence Ciências ambientais Ciência da computação Artificial intelligence
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    Author's mail: antonio.moreno@urv.cat mariadolores.jimenez@urv.cat
    Author identifier: 0000-0003-3945-2314 0000-0001-5544-3210
    Record's date: 2024-09-07
    Papper version: info:eu-repo/semantics/acceptedVersion
    Link to the original source: https://www.worldscientific.com/doi/10.1142/S0218213022410020
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Papper original source: International Journal On Artificial Intelligence Tools. 31 (03):
    APA: Morales Sanchez, Damian; Moreno, Antonio; Jimenez Lopez, M. Dolores; (2022). Machine Learning Methods for Automatic Gender Detection. International Journal On Artificial Intelligence Tools, 31(03), -. DOI: 10.1142/S0218213022410020
    Article's DOI: 10.1142/S0218213022410020
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2022
    Publication Type: Journal Publications

  • Keywords:

    Artificial Intelligence,Computer Science, Artificial Intelligence,Computer Science, Interdisciplinary Applications
    Machine learning
    Gender detection
    Author profiling
    Interdisciplinar
    Engenharias iv
    Engenharias iii
    Computer science, interdisciplinary applications
    Computer science, artificial intelligence
    Ciências ambientais
    Ciência da computação
    Artificial intelligence

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