Abstract
During COVID-19 quarantine, in online sites such as social networks, Gender-Based Violence has alarmingly increased. Online platforms have taken various measures to regulate and prevent broadcasting of violence messages. Multiple proposals based on machine learning and deep learning approaches have been used to address this problem. This work presents an improvement in implementation of a deep learning neural network for detection of Gender-Based Violence in Twitter messages. A total of 32,500 tweets were downloaded from Mexican Twitter accounts and human volunteers manually tagged the tweets as violent and non-violent to be used as training and testing data sets. Experimental results show the effectiveness of the deep neural network (about 90% of the Area Under the Receiver Operating Characteristic) to detect gender violence in Twitter messages using a simple Natural Language Processing approach.
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Miranda, G., Alejo, R., Castorena, C., Rendón, E., Illescas, J., García, V. (2021). Deep Neural Network to Detect Gender Violence on Mexican Tweets. In: Hernández Heredia, Y., Milián Núñez, V., Ruiz Shulcloper, J. (eds) Progress in Artificial Intelligence and Pattern Recognition. IWAIPR 2021. Lecture Notes in Computer Science(), vol 13055. Springer, Cham. https://doi.org/10.1007/978-3-030-89691-1_3
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