Natural Language Processing through BERT for Identifying Gender-Based Violence Messages on Social Media

The purpose of this article is to provide a natural language processing model to classify messages on social media that contain gender violence. The applied methodology considers performing a fine tune process to BERT, so as the output model can be trained with labeled messages -as violence and nonviolence-on the Reddit and Twitter platforms. The performance obtained in terms of area under the curve, accuracy, sensitivity and specificity were 0.9603, 0.8909, 0.8826 and 0.8989 respectively.