AraCovTexFinder: Leveraging the transformer-based language model for Arabic COVID-19 text identification-Reference-Cited by-同舟云学术

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AraCovTexFinder: Leveraging the transformer-based language model for Arabic COVID-19 text identification

Published:2024-07 Issue: Volume:133 Page:107987
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Hossain Md. Rajib^ORCID,Hoque Mohammed Moshiul^ORCID,Siddique Nazmul^ORCID,Dewan M. Ali Akber

Funder

Athabasca University

Publisher

Elsevier BV

Reference54 articles.

1. A deep learning architecture for psychometric natural language processing;Ahmad;ACM Trans. Inf. Syst.,2020

2. Towards COVID-19 fake news detection using transformer-based models;Alghamdi;Knowl.-Based Syst.,2023

3. AraCOVID19-MFH: Arabic COVID-19 multi-label fake news & hate speech detection dataset;Ameur;Procedia Comput. Sci.,2021

4. Actions, answers, and uncertainty: a decision-making perspective on Web-based question answering;Azari;Inf. Process. Manage.,2004

5. Arabic abstractive text summarization using RNN-based and transformer-based architectures;Bani-Almarjeh;Inf. Process. Manage.,2023

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Augmenting sentiment prediction capabilities for code-mixed tweets with multilingual transformers;Social Network Analysis and Mining;2024-04-15

2. Relational Turkish Text Classification Using Distant Supervised Entities and Relations;Computers, Materials & Continua;2024

3. TransNet: Deep Attentional Hybrid Transformer for Arabic Posts Classification;IEEE Access;2024

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