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Enhanced Arabic disaster data classification using domain adaptation.
Moussa, Abdullah M; Abdou, Sherif; Elsayed, Khaled M; Rashwan, Mohsen; Asif, Amna; Khatoon, Shaheen; Alshamari, Majed A.
Afiliación
  • Moussa AM; The Engineering Company for the Development of Digital Systems, Giza, Egypt.
  • Abdou S; Faculty of Computers and Artificial Intelligence, Cairo University, Giza, Egypt.
  • Elsayed KM; Faculty of Computers and Artificial Intelligence, Cairo University, Giza, Egypt.
  • Rashwan M; Faculty of Engineering, Cairo University, Giza, Egypt.
  • Asif A; School of Computing and Communications, Lancaster University Leipzig, Leipzig, Germany.
  • Khatoon S; School of Architecture, Computing & Engineering, University of East London, London, United Kingdom.
  • Alshamari MA; College of Computer Sciences and Information Technology, King Faisal University, AlAhsa, Saudi Arabia.
PLoS One ; 19(4): e0301255, 2024.
Article en En | MEDLINE | ID: mdl-38574077
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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Planificación en Desastres / Desastres / Terremotos / Medios de Comunicación Sociales / Desastres Naturales Límite: Humans Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2024 Tipo del documento: Article País de afiliación: Egipto Pais de publicación: Estados Unidos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Planificación en Desastres / Desastres / Terremotos / Medios de Comunicación Sociales / Desastres Naturales Límite: Humans Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2024 Tipo del documento: Article País de afiliación: Egipto Pais de publicación: Estados Unidos