This research aims to understand this phenomenon to provide insights into how governments can perform better in times of crisis regarding social media and its impact on public opinion. This research aims to understand how social media impacts public perception of government COVID-19 response efforts by studying Facebook comments, likes, and reactions (emoticons).

The study was based on data gathered from Facebook comments on the daily infographic COVID-19 statistics from the official site of the Ministry of Health and Population. The sampling frame is the 52 weeks of 2020, January to December, through random sampling resulting in 546 comments. The comments were analyzed for items including likes, reactions, time of entry, and collection. The data items were analyzed by an AI algorithm and assigned a positive or negative rating (auto-sentiment) which is a byproduct of the sentiment detected and the degree of certainty of that detection. The multiple regression model used to test the two hypotheses showed that both were supported. The study found that the more negative or positive the comment is, the more the number of replies and reactions it receives.

Lastly, a two-step model is suggested to help policymakers address the issue in the future. This policy aims to mitigate the confusion, and semi-regulate online civil discourse. Additionally, analysis of alternative solutions’ inefficiency is displayed to help strengthen the proposed model’s logos.


School of Global Affairs and Public Policy


Public Policy & Administration Department

Degree Name

MA in Public Policy

Graduation Date

Winter 1-31-2023

Submission Date


First Advisor

Rasha Allam

Committee Member 1

Hussein Amin

Committee Member 2

Rana Hendy


124 p.

Document Type

Master's Thesis

Institutional Review Board (IRB) Approval

Not necessary for this item