Detection of violent speech against women in Mexican tweets using an active learning approach

Authors

Keywords:

Violence against women, MLP, Active learning, Twitter, Mexican Spanish Language, Speech violence detection

Abstract

In Latin American and Caribbean States the verbal violence against women on social networks, such as Twitter, is a serious threat that has been addressed through the implementation of social norms, public policies, and social movements. Nevertheless, a challenge is the effective and automatic real-time detection of violent tweets. In this sense, traditional machine learning algorithms have been proposed to tackle social issues where the training process is performed in a static manner. However, considering that Twitter is a dynamic environment where a vast of tweets are generated each second, it requires powerful machine learning algorithms that could exploit this pool of unlabeled data to be incorporated into the model through continuous updates. This paper explores an active learning method based on uncertainty sampling, which identifies the most confusing tweets to be labeled by an expert in real-time. This focused selection prioritizes which data can be used to train a multilayer perceptron that can achieve a better performance with fewer training samples. Experimental results show that including new samples yields promising results, increasing the AUC from 0.8712 to 0.8833.

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Author Biographies

Grisel Miranda-Piña, Instituto Tecnológico de Toluca

Grisel Miranda-Pina is a computer systems engineer graduated from the Tecnológico de Estudios Superiores de Jocotitlán in 2021. She is currently pursuing a Master's Degree in Engineering Sciences at the Tecnológico Nacional de México, Toluca Campus. Among her research interests are the applications of artificial intelligence and artificial neural networks in solving real problems within a big data context.

Roberto Alejo, Tecnológico Nacional de México

Roberto Alejo is a doctor in Advanced Computer Systems from the Universitat Jaume I, Spain. He is currently assigned to the Division of Graduate Studies and Research of the Tecnológico Nacional de México, Toluca Campus. He is also a specialist in artificial neural networks, machine learning and data mining, with a deep scientific interest in the application of artificial intelligence to solve real problems.

Eréndira Rendón-Lara, Instituto Tecnológico de Toluca

Erendira Rendon-Lara is a doctor in Computer Science from the Toluca Technological Institute. She works as a professor-researcher in the Division of Graduate Studies and Research at the Tecnológico Nacional de México, Toluca Campus. Her main academic interests focus on Data Mining and recently on "Material Informatics".

Vicente García, Universidad Autonóma de Ciudad Juárez

Vicente Garcia is a doctor in Advanced Computer Systems from the Universitat Jaume I, Castellón de la Plana, Spain, in 2010. He is currently a full-time professor in the Department of Electrical and Computer Engineering at the Autonomous University of Ciudad Juárez. His research interests include data preprocessing methods, data complexity, non-parametric classification, performance evaluation and big data.

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Published

2024-03-13

How to Cite

Miranda-Piña, G., Alejo, R., Rendón-Lara, E. ., & García, V. (2024). Detection of violent speech against women in Mexican tweets using an active learning approach. IEEE Latin America Transactions, 22(4), 276–285. Retrieved from https://latamt.ieeer9.org/index.php/transactions/article/view/8397

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