Enhanced Arabic disaster data classification using domain adaptation

Moussa, Abdullah M. and Abdou, Sherif and Elsayed, Khaled M. and Rashwan, Mohsen and Asif, Amna and Khatoon, Shaheen and Alshamari, Majed A. (2024) Enhanced Arabic disaster data classification using domain adaptation. PLoS One, 19 (4): e0301255. ISSN 1932-6203

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Abstract

Natural disasters, like pandemics and earthquakes, are some of the main causes of distress and casualties. Governmental crisis management processes are crucial when dealing with these types of problems. Social media platforms are among the main sources of information regarding current events and public opinion. So, they have been used extensively to aid disaster detection and prevention efforts. Therefore, there is always a need for better automatic systems that can detect and classify disaster data of social media. In this work, we propose enhanced Arabic disaster data classification models. The suggested models utilize domain adaptation to provide state-of-the-art accuracy. We used a standard dataset of Arabic disaster data collected from Twitter for testing the proposed models. Experimental results show that the provided models significantly outperform the previous state-of-the-art results.

Item Type:
Journal Article
Journal or Publication Title:
PLoS One
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1100/1100
Subjects:
?? general agricultural and biological sciencesgeneral biochemistry,genetics and molecular biologygeneral medicineagricultural and biological sciences(all)biochemistry, genetics and molecular biology(all)medicine(all) ??
ID Code:
217679
Deposited By:
Deposited On:
15 Apr 2024 12:20
Refereed?:
Yes
Published?:
Published
Last Modified:
16 Jul 2024 12:15