Revista ELECTRO
Vol. 47 – Año 2025
Artículo
TÍTULO
Desarrollo de un Sistema para Identificación de Acoso en Redes Sociales
AUTORES
Villalba-García, A.A.; Nava-Dino, C.G.; Acosta-Chávez, R.A.; Maldonado-Orozco, M.C.; Méndez-Mariscal, N.L.; Aceves, J.M.S; Flores-De los Ríos, J.P.
RESUMEN
En el presente trabajo de investigación se desarrolló un modelo de aprendizaje automático capaz de detectar comportamientos de acoso en redes sociales como X, con el objetivo de facilitar la identificación automática y precisa de comportamientos negativos. Para ello, se utilizó un conjunto de datos de J. Wang (SOSNet, A Graph Convolutional Network Approach to Fine-Grained Cyberbullying Detection) que cuenta con un conjunto de datos de entrenamiento. Se entrenó un modelo BERT para que este pudiera categorizar el texto en alguna de las categorías definidas anteriormente. En los resultados se observa que el sistema implementado, es capaz de identificar entre una variedad de tipos de acoso con un nivel de precisión aceptable.
Palabras Clave: Acoso en Redes, Aprendizaje Automático, Python, Redes Sociales, Comunicaciones.
ABSTRACT
In this research work, a machine learning model capable of detecting harassment behaviors in social networks such as X was developed with the aim of facilitating the automatic and accurate identification of negative behaviors; a dataset from J. Wang (SOSNet, A Graph Convolutional Network Approach to Fine-Grained Cyberbullying Detection) A BERT model was trained to categorize the text into one of the categories defined above. The results obtained by the system, permits identify several types of bullying with acceptable precision.
Keywords: Cyberbullyng, Machine Learning, Python, Social Networks, Comunications.
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CITAR COMO:
Villalba-García, A.A.; Nava-Dino, C.G.; Acosta-Chávez, R.A.; Maldonado-Orozco, M.C.; Méndez-Mariscal, N.L.; Aceves, J.M.S; Flores-De los Ríos, J.P., "Desarrollo de un Sistema para Identificación de Acoso en Redes Sociales", Revista ELECTRO, Vol. 47, 2025, pp. 329-334.
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