ASAVACT: Arabic sentiment analysis for vaccine-related COVID-19 tweets using deep learning
- DOI
- 10.7717/peerj-cs.1507
- Published
- 2023-10-26
- Container
- PeerJ Computer Science
- Publisher
- PeerJ
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.7717/peerj-cs.1507,
title = {ASAVACT: Arabic sentiment analysis for vaccine-related COVID-19 tweets using deep learning},
author = {Sarah Alhumoud and Asma Al Wazrah and Laila Alhussain and Lama Alrushud and Atheer Aldosari and Reema Nasser Altammami and Njood Almukirsh and Hind Alharbi and Wejdan Alshahrani},
year = {2023},
journal = {PeerJ Computer Science},
doi = {10.7717/peerj-cs.1507},
url = {https://doi.org/10.7717/peerj-cs.1507}
}RIS
TY - JOUR TI - ASAVACT: Arabic sentiment analysis for vaccine-related COVID-19 tweets using deep learning AU - Sarah Alhumoud AU - Asma Al Wazrah AU - Laila Alhussain AU - Lama Alrushud AU - Atheer Aldosari AU - Reema Nasser Altammami AU - Njood Almukirsh AU - Hind Alharbi AU - Wejdan Alshahrani PY - 2023 JO - PeerJ Computer Science DO - 10.7717/peerj-cs.1507 UR - https://doi.org/10.7717/peerj-cs.1507 ER -
APA
Alhumoud, S., Wazrah, A. A., Alhussain, L., Alrushud, L., Aldosari, A., Altammami, R. N., Almukirsh, N., Alharbi, H., & Alshahrani, W. (2023). ASAVACT: Arabic sentiment analysis for vaccine-related COVID-19 tweets using deep learning. PeerJ Computer Science. https://doi.org/10.7717/peerj-cs.1507
Source records
- crossref · retrieved 2026-11-09T08:08:11.374Z