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Attention-based networks for analyzing inappropriate speech in Arabic text |
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| Author: | Berrimi, Mohamed1; Moussaoui, Abdelouaheb1; Oussalah, Mourad2; |
| Organizations: |
1dept. of computer science University of Ferhat Abbas 1 Setif, Algeria 2dept. of Computer Science and Engineering University of Oulu, Oulu, Finland 3dept. of Computer Science University of Ferhat Abbas 1, Setif, Algeria |
| Format: | article |
| Version: | accepted version |
| Access: | open |
| Online Access: | PDF Full Text (PDF, 0.1 MB) |
| Persistent link: | http://urn.fi/urn:nbn:fi-fe2021100449274 |
| Language: | English |
| Published: |
Institute of Electrical and Electronics Engineers,
2021
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| Publish Date: | 2021-10-04 |
| Description: |
AbstractAnalyzing social media posts and comments has become a critical task to prevent cyberbullying and hate speech. In this work we present a classification models based on the attention mechanism to analyze Arabic posts and filter out all kinds of inappropriate speech including Religious based hate speech, offensive and abusive content in different Arabic dialects. The attention-based models show promising results for four Arabic datasets. The results are presented and compared in terms of accuracy and training time. see all
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| ISBN: | 978-1-7281-9652-7 |
| ISBN Print: | 978-1-7281-9653-4 |
| Pages: | 1 - 6 |
| Article number: | 9416539 |
| DOI: | 10.1109/ISIA51297.2020.9416539 |
| OADOI: | https://oadoi.org/10.1109/ISIA51297.2020.9416539 |
| Host publication: |
2020 4th International Symposium on Informatics and its Applications (ISIA) |
| Conference: |
International Symposium on Informatics and its Applications (ISIA) |
| Type of Publication: |
A4 Article in conference proceedings |
| Field of Science: |
113 Computer and information sciences |
| Subjects: | |
| Copyright information: |
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