Autores
Huerta Velasco Daniel Abraham
Calvo Castro Francisco Hiram
Título Verbal Aggressions Detection in Mexican Tweets
Tipo Revista
Sub-tipo CONACYT
Descripción Computación y Sistemas
Resumen Verbal aggressions are a struggle that a great number of social media users have to face daily. Some users take advantage of the anonymity that social media give them and offend a person, a group of people, or a concept. The majority of proposals which pretend to detect aggressive comments on social media handle it as a classification problem. Although there are a lot of techniques to face this problem in English, there is a lack of proposals in Spanish. In this work, we propose using several Spanish lexicons which have a collection of words that have been weighted according to different criteria like affective, dimensional, and emotional values. In addition to them, structural values, word embeddings and one-hot codification were taken into account. © 2022 Instituto Politecnico Nacional. All rights reserved.
Observaciones DOI 10.13053/CyS-26-1-4169
Lugar Ciudad de México
País Mexico
No. de páginas 261-269
Vol. / Cap. v. 26 no. 1
Inicio 2022-09-27
Fin
ISBN/ISSN