Author Gender Identification for Short Texts

Authors

  • Francisco Antonio Castillo Velásquez Universidad Politécnica de Querétaro, División de TI, TM y TA
  • José Luis Godoy Martínez Universidad Politécnica de Querétaro, División de TI, TM y TA
  • Jonny Paul Zavala de Paz Universidad Politécnica de Querétaro, División de TI, TM y TA
  • José Amilcar Rizzo Sierra Universidad Politécnica de Querétaro, División de TI, TM y TA
  • María del Consuelo Patricia Torres Falcón Universidad Politécnica de Querétaro, División de TI, TM y TA

DOI:

https://doi.org/10.13053/cys-25-3-3999

Keywords:

Gender identification, machine-learning, n-grams, classification, authorship

Abstract

At present, the possibility of communicating or expressing oneself through an electronic medium is very wide: most users of computers and mobile devices use email, social networks, chats and other tools. One of the problems that has arisen with this form of communication is excess, such as plagiarism, false identity, intimidating notes, and others. The attribution of authorship of texts (AAT) is responsible for answering the question of who is the author of a text, giving some previous examples of that author (training set). A useful process within the AAT is the identification of gender or sex (male, female) and that has been studied by several authors, but mainly for English. The present work proposes a computational model based on lexical characteristics (n-grams) for the identification of the genre for short texts in Spanish. Tests were made with a corpus of text messages on social networks and blogs, obtaining promising results.

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Published

2021-08-18

Issue

Vol. 25 No. 3 (2021): 25(3) 2021

Section

Articles

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