Previously submitted to: JMIR Public Health and Surveillance (no longer under consideration since May 12, 2021)
Date Submitted: Mar 11, 2021
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Government use of Twitter during the COVID-19 pandemic by five ministries in Saudi Arabia: a content analysis of tweets
ABSTRACT
Background:
Government public communication during the COVID-19 pandemic in the form of Twitter messages has a potential role in influencing the public response to the pandemic. Understanding the collective efforts by governmental ministries is vital in recognizing the mechanisms, by which the use of Twitter for governmental communication was expected to guide appropriate coordinated actions.
Objective:
To examine topics related to COVID-19 posted by Saudi governmental ministries on Twitter by conducting a content analysis. We also aim to further analyze the generated topics by situating our findings within the Saudi context and existing health behavior theoretical frameworks.
Methods:
We performed a retrospective content analysis of COVID-19 related tweets. On November 7th, 2020 we extracted relevant tweets posted by five Saudi governmental ministries. Our study was conducted in three phases: (1) data extraction, preparation, and transformation (2) coding schema development and application, and (3) analysis. To give context to the generated topics we considered the COVID-19 pertinent social events in Saudi Arabia and divided the social events into four phases according to the Crisis, Emergency, Risk Communication (CERC) Rhythm. We used constructs of key health behavioral theories to further examine the “empowerment” category.
Results:
A total of 3,950 tweets were included in our dataset. Topics fell into two groups: disease related (49.2%) and non-disease related (50.8%). The disease-related group included seven categories: awareness (18.5%), symptom (0.6%), prevention (7.7%), disease transmission (1.9%), treatment (0.3%), testing (3.4%), and reports (16.7%). The non-disease related group included eight categories: lockdown (5.9%), online learning (12.8%), digital platforms (4.3%), empowerment (12.0%), accountability (1.1%), non-disease reports (2.1%), local and international news (10.8%), and general statements (1.9%). Based on the correlation analysis, we found that the top positively correlated categories were: “testing” and “digital platforms” (r = 0.4157), “awareness” and “prevention” (r=0.3088), “prevention” and “disease transmission” (r=0.3025), “awareness” and “disease transmission” (r=0.1685), “symptom” and “testing” (r=0.1081), “awareness” and “symptom” (r=0.0812), “symptom” and “digital platforms” (r=0.0645), and “disease transmission” and “digital platforms” (r=0.0450), p-values < 0.01. Within the Saudi context as it relates to CERC, “awareness” was the top frequent category during the “preparation” and “maintenance” phases, while “empowerment” was the top category during the “initiation” phase and “online learning” was the top category during the “resolution” phase. There was a number of health behavior theoretical constructs linked to our findings including: perceived benefits, perceived severity, perceived behavioral control, observational learning, incentive motivation, self-efficacy, collective efficacy, and facilitation.
Conclusions:
Social media platforms can be utilized as powerful tools to communicate with the public during a health crisis. Integrating behavioral theories in the development of health risk communication should be taken seriously by government communication specialists who manage social media accounts, as these theories help underlining determinants of people’s behaviors.
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