Comparative Performance of Machine Learning and Deep Learning Algorithms for Arabic Hate Speech Detection in OSNs-Reference-Cited by-同舟云学术

Comparative Performance of Machine Learning and Deep Learning Algorithms for Arabic Hate Speech Detection in OSNs

Published:2020 Issue: Volume: Page:247-257
ISSN:2194-5357
Container-title:Advances in Intelligent Systems and Computing
language:
Short-container-title:

Author:

Omar Ahmed^ORCID,Mahmoud Tarek M.,Abd-El-Hafeez Tarek^ORCID

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-44289-7_24

Reference21 articles.

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3. Alakrot, A., Murray, L., Nikolov, N.S.: Towards accurate detection of offensive language in online communication in Arabic. Procedia Comput. Sci. 142, 315–320 (2018)

4. Albadi, N., Kurdi, M., Mishra, S.: Are they our brothers? Analysis and detection of religious hate speech in the Arabic Twittersphere. In: Proceedings of the 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining. ASONAM 2018, pp. 69–76 (2018)

5. Bodkhe, R., Ghorpade, T., Jethani, V.: A novel methodology to filter out unwanted messages from OSN user’s wall using trust value calculation. In: Satapathy, S.C., Raju, K.S., Mandal, J.K., Bhateja, V. (eds.) Proceedings of the Second International Conference on Computer and Communication Technologies, pp. 755–764. Springer, New Delhi (2016)

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