Abstract
Nowadays, policy makers face complex challenges such as cybersecurity, infectious disease control, and political rumors, which can quickly elicit large-scale crises in a world connected by social media. However, scarce work is found in using social media analytics to support high-impact policy areas that span across nations and population groups. In this chapter, we describe a framework for social-media-based policy informatics and its application to addressing policy issues concerned by governments and general public. Based on the framework, we conducted two case studies: The first study concerns with the U.S. immigration and border security, which is increasingly motivated by cyber means and affects the U.S. economy, national security, and foreign policies. The second study concerns with the West African Ebola disease outbreak, which has caused over 11,305 people to die and is the largest and most complex in the history of the disease. We present empirical findings obtained from the data analyses and discuss the implication for public policy decision making. The research should contribute to developing a new social-media-based framework for policy informatics and to demonstrating its use in high-impact policy issues.
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Abbreviations
- BBC:
-
British Broadcasting Company
- BI:
-
Business intelligence
- D.C.:
-
District of Columbia
- eMood:
-
Ebola disease outbreak social media mood system
- iMood:
-
The U.S. immigration and border security mood system
- MIS:
-
Management information systems
- SM:
-
Social media
- SMA:
-
Social media analytics
- U.C.F.:
-
University of Central Florida
- U.S.:
-
United States
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Chung, W., Zeng, D. (2018). Social-Media-Based Policy Informatics: Cyber-Surveillance for Homeland Security and Public Health Informatics. In: Gil-Garcia, J., Pardo, T., Luna-Reyes, L. (eds) Policy Analytics, Modelling, and Informatics. Public Administration and Information Technology, vol 25. Springer, Cham. https://doi.org/10.1007/978-3-319-61762-6_16
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