Identifying Instances of Cyberbullying on Twitter Using Deep Learning
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-6984-5_6
Reference12 articles.
1. Wang, J., Fu, K., Lu, C.T. (2023). SOSNet: A graph convolutional network approach to fine-grained cyberbullying detection. In Proceedings of the 2020 IEEE international conference on big data (IEEE bigdata 2020). Retrieved 8 February 2023 from https://www.kaggle.com/datasets/andrewmvd/cyberbullying-classification
2. Venkataramanan, K. (2018). Classification of cyber-bullying using convolution neural network. IJARCCE, 7, 65–70. https://doi.org/10.17148/IJARCCE.2018.71215
3. Alsubari, S. (2022). Cyberbullying identification system based deep learning algorithms. Electronics. https://doi.org/10.3390/electronics11203273
4. Behzadi, M., Harris, I. G., & Derakhshan, A. (2021). Rapid cyber-bullying detection method using compact BERT models. In 2021 IEEE 15th international conference on semantic computing (ICSC), Laguna Hills, CA, USA (pp. 199–202). https://doi.org/10.1109/ICSC50631.2021.00042
5. Yadav, J., Kumar, D., & Chauhan, D. (2020). Cyberbullying detection using pre-trained BERT model. In 2020 international conference on electronics and sustainable communication systems (ICESC), Coimbatore, India (pp. 1096–1100). https://doi.org/10.1109/ICESC48915.2020.9155700
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