The Text Mining of Public Policy Documents in Response to COVID-19: A Comparison of the United Arab Emirates and the Kingdom of Saudi Arabia


Abstract

Objective: The objective of the paper is to analyse publicly available government policy documents of the United Arab Emirates (UAE) and the Kingdom of Saudi Arabia (KSA) in order to identify key topics and themes for these two countries in relation to the COVID-19 response.

Research Design & Methods: In view of the availability of large volumes of documents as well as advancement in computing system, text mining has emerged as a significant tool to analyse large volumes of unstructured data. For this paper, we have applied latent semantic analysis and Singular Value Decomposition (SVD) for text clustering.

Findings: The results of the analysis of terms indicate similarities of key themes around health and pandemic for the UAE and the KSA. However, the results of text clustering indicate that focus of the UAE’ documents in on ‘Digital’-related terms, whereas for the KSA, it is around ‘International Travel’-related terms. Further analysis of topic modelling demonstrates that topics such as ‘Vaccine Trial’, ‘Economic Recovery’, ‘Health Ministry’, and ‘Digital Platforms’ are common across both the UAE and the KSA.

Contribution / Value Added: The study contributes to text-mining literature by providing a framework for analyzing public policy documents at the country level. This can help to understand the key themes in policies of the governments and can potentially aid the identification of the success and failure of various policy measures in certain cases by means of comparing the outcomes.

Implications / Recommendations: The results of this study clearly showed that text clustering of unstructured data such as policy documents could be very useful for understanding the themes and orientation topics of the policies.

Article classification: research paper

JEL classification: D78, E61, I18, L38


Keywords

text mining; COVID-19; public policy; information extraction; topic modelling; text clustering

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Appendix
Various government entities and media reports citing government actions as the COVID-19 response have been taken from the following websites:
• UAE Embassy https://www.uae-embassy.org/
• Federal Authority for Identity and Citizenship (ICA) https://smartservices.ica.gov.ae/
• Ministry of Foreign Affairs https://www.mofaic.gov.ae/
• News and Media: https://www.khaleejtimes.com/
• News and Media: https://english.alarabiya.net
• News and Media: https://gulfnews.com
• News and Media: https://www.meed.com/
• News and Media https://www.arabnews.com/
• News and Media https://www.reuters.com/
• Ministry of Health and Preventions: https://www.mohap.gov.ae/
• News and Media: http://wam.ae/
• News and Media: https://www.jdsupra.com/
• News and Media: https://www.aljazeera.com/
• National emergency crisis and disaster recovery: https://www.ncema.gov.ae/
• Privately owned security services company: https://www.garda.com/
• Community platform for real estate: https://bldgtmrw.com/
• News and Media: https://www.cnbc.com/
• The National Emergency Crisis and Disasters Management Authority’s platform: http://www.weqaya.ae/
• News and Media: https://www.caixinglobal.com/
• Ministry of Health KSA initiative: https://covid19awareness.sa
• News and Media: https://www.bbc.com/
• International Monetary Fund: https://www.imf.org/
• Ministry of Health KSA: https://www.moh.gov.sa/
• Saudi Arabia Monetary Authority: http://www.sama.gov.sa/
• News and Media: https://www.atlas-mag.net/
• News and Media: https://thearabweekly.com/
• The Saudi Data and Artificial Intelligence Authority: https://sdaia.gov.sa/
• Integrated encyclopedia: https://mhtwyat.com/
• Johns Hopkins Aramco healthcare: https://www.jhah.com/
• Saudi Press Agency: https://www.spa.gov.sa/
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Published : 2021-12-21


Dwivedi, D. N., & Anand, A. (2021). The Text Mining of Public Policy Documents in Response to COVID-19: A Comparison of the United Arab Emirates and the Kingdom of Saudi Arabia. Public Governance / Zarządzanie Publiczne, 55(1), 8-22. https://doi.org/10.15678/ZP.2021.55.1.02

Dwijendra Nath Dwivedi 
EMEA AI and IOT Leader at SAS Institute  United Arab Emirates

Dubai


Abhishek Anand 
Credit Risk Team, HSBC  Poland
https://orcid.org/

Kraków



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