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Developing a COVID-19 Crisis Management Strategy Using News Media and Social Media in Big Data Analytics
- Source :
- Social Science Computer Review. 40:1358-1375
- Publication Year :
- 2021
- Publisher :
- SAGE Publications, 2021.
-
Abstract
- Due to the unpredictability of global events such as a COVID-19 pandemic, it is necessary to prepare for a crisis management strategy at the macro-level in each country to respond to crises that bring about social change. This study is designed to discover critical priorities and agendas in crisis management in Saudi Arabia by grasping the most recent social issues of the COVID-19 pandemic addressed in the most trusted media sources. The data were collected from news media (Saudi Press Agency and Al Arabiya) and social media (Twitter and YouTube) in big data from February to August 2020, then analyzed through semantic network analysis. This study provides the uncanny and marvelous power to help any individual, organization, even society, and country to be more innovative and proactive by acquiring trend, agenda-based approaches into uncertain future crises using advanced technology in big data. This research also shows how a country can use those big data to detect “key social issues” and then make a subsequent strategy or decision-making system to develop a public communication or new policy in future events. Accordingly, this study provides meaningful and insightful implications for managing a coming crisis and social change, ensuring stability and sustainability at the micro- and macro-level.
- Subjects :
- 2019-20 coronavirus outbreak
Coronavirus disease 2019 (COVID-19)
business.industry
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
Big data
General Social Sciences
Crisis management
Library and Information Sciences
Public relations
Computer Science Applications
Pandemic
Social media
Business
Law
News media
Subjects
Details
- ISSN :
- 15528286 and 08944393
- Volume :
- 40
- Database :
- OpenAIRE
- Journal :
- Social Science Computer Review
- Accession number :
- edsair.doi...........13671d6563ce700859535058227147da
- Full Text :
- https://doi.org/10.1177/08944393211007314