Recognition and Classification of Hate Messages

The massive use of social networks and the anonymity that this provides has made possible not only the immediate communication between users, but also the spread of hate speech against certain groups of our society in the form of offensive messages to them, this has led to a serious social problem,...

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Bibliographic Details
Authors: Paredes Neira, Patrick Leopoldo, Vilca Tapia, Gary Jamil, Lazarte Zubia, Kristhyan Andree Kurt
Format: article
Status:Published version
Publication Date:2023
Country:Perú
Institution:Universidad La Salle
Repository:Revistas - Universidad La Salle
Language:Spanish
OAI Identifier:oai:ojs.revistas.ulasalle.edu.pe:article/99
Online Access:https://revistas.ulasalle.edu.pe/innosoft/article/view/99
https://doi.org/10.48168/innosoft.s12.a99
https://purl.org/42411/s12/a99
https://n2t.net/ark:/42411/s12/a99
Access Level:Open access
Keyword:Hate
HateCheck
Hate Speech Detection Models
NLP
Natural Language Processing
Hate Speech
Spanish Processing
Odio
Modelos de Detección del Discurso de Odio
Procesamiento del Lenguaje Natural
Discurso de Odio
Procesamiento del Español
Description
Summary:The massive use of social networks and the anonymity that this provides has made possible not only the immediate communication between users, but also the spread of hate speech against certain groups of our society in the form of offensive messages to them, this has led to a serious social problem, which remains a topic of current research along with NLP. The purpose of the present work is to make a comparison of our "HateCheck" recognition model against the author's results, using the same database as them. To do so, we will make use of the main metrics such as: precision, recall and F1.