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Fusion: Practice and Applications
Volume 14 , Issue 2, PP: 227-243 , 2024 | Cite this article as | XML | Html |PDF

Title

Analyzing Social Media Data to Understand Long-Term Crisis Management Challenges of COVID-19

  Ali S. Abed Al Sailawi 1 * ,   Mohammad Reza Kangavari 2

1  College of Law, University of Misan, Amarah, Iraq
    (a_alsailawi@cmps2.iust.ac.ir)

2  School of Computer Engineering, Iran University of Science and Technology, Tehran, Iran
    (kangavari@iust.ac.ir)

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Doi   :   https://doi.org/10.54216/FPA.140219

Received: July 12, 2023 Revised: December 02, 2023 Accepted: January 29, 2024

Abstract :

In the past three years, social media has had a significant impact on our lives, including crisis management. The COVID-19 pandemic highlighted the importance of accurate information and exposed the spread of false information. This paper specifically examines the COVID-19 crisis and analyzes relevant literature to provide insights for national authorities and organizations. Utilizing social media data for crisis management poses challenges due to its unstructured nature. To overcome this, the paper proposes a comprehensive method that addresses all aspects of long-term crisis management. This method relies on labeled and structured information for accurate sentiment analysis and classification. An automated approach is presented to annotate and classify tweet texts, reducing manual labeling and improving classifier accuracy. The framework involves generating topics using Latent Dirichlet Allocation (LDA) and ranking them with a new algorithm for data annotation. The labeled text is transformed into feature representation using Bert embeddings, which can be utilized in deep learning models for categorizing textual data. The primary aim of this paper is to offer valuable insights and resources to researchers studying crisis management through social media literature, with a specific focus on high-accuracy sentiment analysis.

Keywords :

COVID-19 pandemic; Social Medias; Long-Lasting Crisis Management.

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Cite this Article as :
Style #
MLA Ali S. Abed Al Sailawi, Mohammad Reza Kangavari. "Analyzing Social Media Data to Understand Long-Term Crisis Management Challenges of COVID-19." Fusion: Practice and Applications, Vol. 14, No. 2, 2024 ,PP. 227-243 (Doi   :  https://doi.org/10.54216/FPA.140219)
APA Ali S. Abed Al Sailawi, Mohammad Reza Kangavari. (2024). Analyzing Social Media Data to Understand Long-Term Crisis Management Challenges of COVID-19. Journal of Fusion: Practice and Applications, 14 ( 2 ), 227-243 (Doi   :  https://doi.org/10.54216/FPA.140219)
Chicago Ali S. Abed Al Sailawi, Mohammad Reza Kangavari. "Analyzing Social Media Data to Understand Long-Term Crisis Management Challenges of COVID-19." Journal of Fusion: Practice and Applications, 14 no. 2 (2024): 227-243 (Doi   :  https://doi.org/10.54216/FPA.140219)
Harvard Ali S. Abed Al Sailawi, Mohammad Reza Kangavari. (2024). Analyzing Social Media Data to Understand Long-Term Crisis Management Challenges of COVID-19. Journal of Fusion: Practice and Applications, 14 ( 2 ), 227-243 (Doi   :  https://doi.org/10.54216/FPA.140219)
Vancouver Ali S. Abed Al Sailawi, Mohammad Reza Kangavari. Analyzing Social Media Data to Understand Long-Term Crisis Management Challenges of COVID-19. Journal of Fusion: Practice and Applications, (2024); 14 ( 2 ): 227-243 (Doi   :  https://doi.org/10.54216/FPA.140219)
IEEE Ali S. Abed Al Sailawi, Mohammad Reza Kangavari, Analyzing Social Media Data to Understand Long-Term Crisis Management Challenges of COVID-19, Journal of Fusion: Practice and Applications, Vol. 14 , No. 2 , (2024) : 227-243 (Doi   :  https://doi.org/10.54216/FPA.140219)
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