Enhancing Cyberbullying Detection on Indonesian Twitter: Leveraging FastText for Feature Expansion and Hybrid Approach Applying CNN and BiLSTM

Cyberbullying, characterized by the transmission of threatening, intimidating, and derogatory messages via digital platforms such as Twitter, is a pervasive issue. Given the volume of approximately 867 million daily tweets, the potential scale of cyberbullying incidents is immense, underscoring the...

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Veröffentlicht in:	Revue d'Intelligence Artificielle 2023-08, Vol.37 (4), p.929-936
Hauptverfasser:	Nasution, Muhammad Alfi Syahri, Setiawan, Erwin Budi
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Artificial neural networks Bullying Classification Cyberbullying Datasets Deep learning Information retrieval Internet service providers Labeling Language Languages Machine learning Messages Research methodology Slang Social networks Supervised learning Support vector machines
Online-Zugang:	Volltext
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