Shielding Social Media: BERT and SVM Unite for Cyberbullying Detection and Classification

  • Parth Aggarwal Pathways World School Gurgaon, India
  • Rhea Mahajan University of Jammu, India
Keywords: Cyberb ully;BERT; SVM; SHAP; XAI

Abstract

This paper presents a novel approach for cyberbullying detection and classification in social media text using an ensemble model that combines BERT (Bidirectional Encoder Representations from Transformers) and Support Vector Machine (SVM) with grid search for multiclass classification. We have also compared the performance of our proposed with various machine and deep learning models and the results show that our proposed model outperforms other models achieving an accuracy of 90% on testing data. Further, we have used to used SHapley Additive exPlanations (SHAP) an Explainable (XAI) technique to interpret the predictions of the BERT-SVM ensemble model.

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Published
2024-06-12
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How to Cite
Aggarwal, P., & Mahajan, R. (2024). Shielding Social Media: BERT and SVM Unite for Cyberbullying Detection and Classification. Journal of Information Systems and Informatics, 6(2), 607-623. https://doi.org/10.51519/journalisi.v6i2.692