Hybrid Convolutional Recurrent Neural Network for Cyberbullying Detection on Textual Data

Baiganova A. Toxanova S. Yerekesheva M. Nauryzova N. Zhumagalieva Z. Tulendi A.
2024 Science and Information Organization

International Journal of Advanced Computer Science and Applications
2024 #15 Issue 5 834 - 842 pp.

With the burgeoning use of social media platforms, online harassment and cyberbullying have become significant concerns. Traditional mechanisms often falter, necessitating advanced methodologies for efficient detection. This study presents an innovative approach to identifying cyberbullying incidents on social media sites, employing a hybrid neural network architecture that amalgamates Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN). By harnessing the sequential processing capabilities of LSTM to analyze the temporal progression of textual data, and the spatial discernment of CNN to pinpoint bullying keywords and patterns, the model demonstrates substantial improvement in detection accuracy compared to extant methods. A diverse dataset, encompassing multiple social media platforms and linguistic styles, was utilized to train and test the model, ensuring robustness. Results evince that the LSTM-CNN amalgamation can adeptly handle varied sentence structures and contextual nuances, outstripping traditional machine learning classifiers in both specificity and sensitivity. This research underscores the potential of hybrid neural networks in addressing contemporary digital challenges, urging further exploration into blended architectures for nuanced problem-solving in cyber realms.

CNN , impulsive sounds , LSTM , RNN , urban sounds

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Zhubanov Aktobe Regional University, Aktobe, Kazakhstan
L.N. Gumilyov Eurasian National University, Astana, Kazakhstan
Kazakh National Women’s Teacher Training University, Almaty, Kazakhstan

Zhubanov Aktobe Regional University
L.N. Gumilyov Eurasian National University
Kazakh National Women’s Teacher Training University

10 лет помогаем публиковать статьи Международный издатель

Книга Публикация научной статьи Волощук 2026 Book Publication of a scientific article 2026