A Lightweight Machine Learning Model for Early Detection of Cyberbullying in Online Gaming Communities to Support Digital Character Education
DOI:
https://doi.org/10.51276/edu.v7i2.1650Keywords:
Cyberbullying , Digital Character education , Digital Literacy , Linear SVM , Slang NormalizationAbstract
This study develops a lightweight early-warning model to identify toxic utterances as practical indicators of cyberbullying in Indonesian-language conversations within the Roblox gaming community, to support digital character education and child online safety. A corpus of 2,798 publicly available comments was manually annotated into Safe and Toxic categories and divided into training and testing sets. Text preprocessing included case folding, noise removal, tokenization, Roblox-specific slang normalization, stemming, and stopword removal. Text features were represented using term frequency–inverse document frequency (TF-IDF) unigram–bigram vectors. A linear Support Vector Machine (SVM) was evaluated against Multinomial Naïve Bayes as a baseline model. Results from hold-out testing indicate that the SVM achieved 82.14% accuracy and a macro-F1 score of 0.82, outperforming the baseline. Cross-validation results show performance variability, highlighting the need for continuous updates of domain-specific slang resources and broader data coverage. From an educational perspective, the proposed prototype can function as a non-punitive screening tool to support digital literacy instruction, school counselling, and parental mediation within a human-in-the-loop framework.
Downloads
References
Balakrisnan, V., & Kaity, M. (2023). Cyberbullying Detection and Machine Learning: A Systematic Literature Review. Artificial Intelligence Review, 56(Suppl 1), 1375–1416. https://doi.org/10.1007/s10462-023-10553-w
Bustamin, A., Prayogi, A. A., Siswanto, D., Rafrin, M., & Nurdin, A. (2025). Text Normalization for Indonesian Slang Words in Sentiment Analysis Development. ICIC Express Letters, Part B: Applications, 16(2), 121–129. https://doi.org/10.24507/icicelb.16.02.121
Candra, A., Wella, & Wicaksana, A. (2021). Bidirectional Encoder Representations from Transformers for Cyberbullying Text Detection in Indonesian Social Media. International Journal of Innovative Computing, Information and Control, 17(5), 1599–1615. https://doi.org/10.24507/ijicic.17.05.1599
Chan, N. N., Samsudin, N., Hoo, M. C., Ridzuan, M. I. B. M., Ooi, P. B., Mohamad, A. M. A. M., & Scheithauer, H. (2023). The Digital Defence against Cyberbullying: A Systematic Review of Tech-Based Approaches. Cogent Education, 10(2), 2288492. https://doi.org/10.1080/2331186X.2023.2288492
Cortes, C., & Vapnik, V. (1995). Support-Vector Networks. Machine Learning, 20(3), 273–297. https://doi.org/10.1007/BF00994018
Elisabeth, D., Budi, I., & Ibrohim, M. O. (2020). Hate Code Detection in Indonesian Tweets Using Machine Learning Approach: A Dataset and Preliminary Study. In 2020 8th International Conference on Information and Communication Technology (ICoICT) (pp. 1–6). IEEE. https://doi.org/10.1109/ICoICT49345.2020.9166251
Findawati, Y., Raharjo, A. B., Navastara, D. A., Yonathan, V., Yatestha, A. A., & Purwitasari, D. (2025). Multi-Label Aspect Dangerous Speech Classification Using Keyword-Driven Ensemble Classifier on Imbalanced Data. JOIV: International Journal on Informatics Visualization, 9(4), 3129. https://doi.org/10.62527/joiv.9.4.3129
Hibatullah, H., Ballı, T., & Yetkin, E. F. (2025). Verbal Harassment Detection in Online Games Using Machine Learning Methods. Entertainment Computing, 55, 101009. https://doi.org/10.1016/j.entcom.2025.101009
Hu, Y., Clancy, E. M., & Klettke, B. (2025). Player versus Player: A Systematic Review of Cyberbullying in Multiplayer Online Games. Computers in Human Behavior Reports, 18, 100675. https://doi.org/10.1016/j.chbr.2025.100675
Ibrohim, M. O., & Budi, I. (2023). Hate Speech and Abusive Language Detection in Indonesian Social Media: Progress and Challenges. Heliyon, 9(8), e18647. https://doi.org/10.1016/j.heliyon.2023.e18647
Ismail, M., Jones, B. C., & Fadzil, A. F. (2025). Enhancing Online Toxicity Detection on Gaming Networks: A Multi-Feature, Lightweight Approach. Crime Science, 14(1), 2. https://doi.org/10.1007/s41060-025-00730-1 ⚠️
Isnawan, F. (2025). Pencegahan Cyberbullying melalui Pendidikan Karakter dan Pendidikan Hukum bagi Siswa Sekolah. Jurnal Civic Hukum, 10(1). https://doi.org/10.22219/jch.v10i1.36879
Joachims, T. (1998). Text Categorization with Support Vector Machines: Learning with Many Relevant Features. In Proceedings of the 10th European Conference on Machine Learning (ECML 1998) (pp. 137–142). Springer. https://doi.org/10.1007/BFb0026683
Kusuma, R., & Nugroho, A. (2024). Deteksi Cyberbullying pada Media Sosial Twitter Menggunakan Algoritma Support Vector Machine (SVM). JUTIF: Jurnal Teknik Informatika, 5(1). https://doi.org/10.52436/1.jutif.2024.5.1.809
Marciano, L., Schulz, P. J., & Camerini, A.-L. (2020). Cyberbullying Perpetration and Victimization in Youth: A Meta-Analysis of Longitudinal Studies. Journal of Computer-Mediated Communication, 25(2), 163–181. https://doi.org/10.1093/jcmc/zmz031
Nabiilah, G. Z., Prasetyo, S. Y., Izdihar, Z. N., & Girsang, A. S. (2023). BERT Base Model for Toxic Comment Analysis on Indonesian Social Media. Procedia Computer Science, 216, 714–721. https://doi.org/10.1016/j.procs.2022.12.188
Naseem, U., Shiwakoti, S., Shah, S. B., Thapa, S., & Zhang, Q. (2025). GameTox: A Comprehensive Dataset and Analysis for Enhanced Toxicity Detection in Online Gaming Communities. In Proceedings of the 2025 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL) (pp. 440–447). https://doi.org/10.18653/v1/2025.naacl-short.37
Pamungkas, E. W., & Chiril, P. (2025). Ngalawan Ujaran Sengit: Hate Speech Detection in Indonesian Code-Mixed Social Media Data. Language Resources and Evaluation, 59, 2387–2414. https://doi.org/10.1007/s10579-025-09810-x
Polanin, J. R., Espelage, D. L., & Grotpeter, J. K. (2022). A Systematic Review and Meta-Analysis of Interventions to Decrease Cyberbullying Perpetration and Victimization. Prevention Science, 23(3), 439–454. https://doi.org/10.1007/s11121-021-01259-y
Putri, S. D. A., Ibrohim, M. O., & Budi, I. (2021). Abusive Language and Hate Speech Detection for Javanese and Sundanese Languages in Tweets: Dataset and Preliminary Study. In Proceedings of the 2021 International Conference on World Computing and Software Engineering (WCSE) (pp. 67–72). https://doi.org/10.18178/wcse.2021.02.011
Susanto, L., Wijanarko, M. I., Pratama, P. A., Tang, Z., Akyas, F., Hong, T., Idris, I. K., Aji, A. F., & Wijaya, D. T. (2025). A Multi-Labeled Dataset for Indonesian Discourse: Examining Toxicity, Polarization, and Demographics Information. In Findings of the Association for Computational Linguistics: ACL 2025 (pp. 18863–18890). https://doi.org/10.18653/v1/2025.findings-acl.966
Tozzo, P., Cuman, O., Moratto, E., & Caenazzo, L. (2022). Family and Educational Strategies for Cyberbullying Prevention: A Systematic Review. International Journal of Environmental Research and Public Health, 19(16), 10452. https://doi.org/10.3390/ijerph191610452
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Farhan Badrani, Nuur Wachid Abdul Majid

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.


































