Comparative Performance of Multi-level Pre-trained Embeddings on CNN, LSTM and CNN-LSTM for Hate Speech and Offensive Language Detection-Reference-Cited by-同舟云学术

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Comparative Performance of Multi-level Pre-trained Embeddings on CNN, LSTM and CNN-LSTM for Hate Speech and Offensive Language Detection

Published:2024 Issue: Volume: Page:186-195
ISSN:2367-3370
Container-title:Lecture Notes in Networks and Systems
language:en
Short-container-title:

Author:

Aziz Noor Azeera Abdul,Zainal Anazida,Al-Rimy Bander Ali Saleh,Ghaleb Fuad Abdulgaleel Abdoh

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-66965-1_19

Reference27 articles.

1. Twitter: “Twitter Rules and Policies (2020). [Online]. https://help.twitter.com/en/rules-and-policies/hateful-conduct-policy. Accessed 30-Dec-2020

2. Facebook: Community Standards (2020). [Online]. https://www.facebook.com/communitystandards/hate_speech. Accessed: 30-Dec-2020

3. YouTube: Community Guidelines (2020). [Online]. https://support.google.com/youtube/answer/2801939?hl=en. Accessed: 30-Dec-2020

4. Bengio, Y., Ducharme, R., Vincent, P.: A neural probabilistic language model. J. Mach. Learn. Res. 3(6), 1137–1155 (2003)

5. Zulqarnain, M., Ghazali, R., Mazwin, Y., Hassim, M., Rehan, M.: A comparative review on deep learning models for text classification. Indones. J. Electr. Eng. Comput. Sci. 19(1), 325–335 (2020)

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