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DOI: 10.14569/IJACSA.2020.0111018

A Comparison of Classification Models to Detect Cyberbullying in the Peruvian Spanish Language on Twitter

Author 1: Ximena M. Cuzcano
Author 2: Victor H. Ayma

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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 11 Issue 10, 2020.

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Abstract: Cyberbullying is a social problem in which bullies’ actions are more harmful than in traditional forms of bullying as they have the power to repeatedly humiliate the victim in front of an entire community through social media. Nowadays, multiple works aim at detecting acts of cyberbullying via the analysis of texts in social media publications written in one or more languages; however, few investigations target the cyberbullying detection in the Spanish language. In this work, we aim to compare four traditional supervised machine learning methods performances in detecting cyberbullying via the identification of four cyberbullying-related categories on Twitter posts written in the Peruvian Spanish language. Specifically, we trained and tested the Naive Bayes, Multinomial Logistic Regression, Support Vector Machines, and Random Forest classifiers upon a manually annotated dataset with the help of human participants. The results indicate that the best performing classifier for the cyberbullying detection task was the Support Vector Machine classifier.

Keywords: Cyberbullying detection; machine learning; natural language processing; feature extraction

Ximena M. Cuzcano and Victor H. Ayma, “A Comparison of Classification Models to Detect Cyberbullying in the Peruvian Spanish Language on Twitter” International Journal of Advanced Computer Science and Applications(IJACSA), 11(10), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0111018

@article{Cuzcano2020,
title = {A Comparison of Classification Models to Detect Cyberbullying in the Peruvian Spanish Language on Twitter},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0111018},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0111018},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {10},
author = {Ximena M. Cuzcano and Victor H. Ayma}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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