# A Retrospective Analysis of the COVID-19 Infodemic in Saudi Arabia
## 5 Discussion  
This study aimed to address the following research questions: (1) What forms of misinformation spread the most in pandemics? (2) How does misinformation evolve over time? In this current research, a retrospective analysis of the COVID-19 infodemic was conducted concerning the country of Saudi Arabia. According to the three basic research questions, our major contributions can be summarized as follows: (1) We extracted a sample of tweets from a large Arabic dataset related to the COVID-19 pandemic from December 2019 to April 2020. Human annotators were utilized for labeling the sample for this purpose. (2) We utilized quantitative and qualitative methodologies including Twitter data and survey results to understand public opinion toward misinformation. (3) We discussed the findings through the lens of the local context in Saudi Arabia and looked at how misinformation is spread depending on the culture, laws, and period of time. Regarding the first research question, the narrative threads of misinformation that have circulated in Saudi Arabia since the COVID-19 pandemic include the origin of COVID-19 and health advice coping with COVID-19. The findings suggest that misinformation could be tied in with sense-making, which is consistent with previous research [1; 2]. It has been concluded that people turn to rumors as a way to cope with uncertainty. Moreover, the types of misinformation that were shared included health-related rumors and political issues, which could indicate that the public is more interested in these subjects and is willing to believe and share such information without validating it with an authentic source. In general, online platforms provide a venue for finding and sharing health information [34; 35]. It is worth noting that the government's prompt response to the pandemic spread of disinformation has aided in limiting the transmission of misinformation to the public and reducing the duration of rumors among individuals. This consistent information was also reported by other research work for the African subcontinent [36]. In addressing the second research question, this paper identifies temporal patterns of misinformation. It can be observed from Figure 3 that multiple misinformation items appeared in the mid-set of the pandemic with a quick turnaround of misinformation as the perception of Islamophobia and conspiracy theories. Moreover, it can also be noticed from Figure 3 that there is no single pattern for how misinformation is shared in the community; however, it is evident that it takes a couple of rounds of sharing before it times out. Further examining the results, the weekly growth of misinformation demonstrated that the biological war exhibits the highest value of the thematic one compared to the others. Moreover, the other pandemic set showed quite similar responses in the time run; albeit, a little scatter was observed for Islamophobia, health advice, and conspiracy theories of thematic categories in the digital misinformation systems. Such responses in the results of misinformation growth might lead to the fact that the mean respondent has disseminated the most in social media via Tweets. It was evident that misinformation presents a severe risk to public health and public action. This finding is in line with WHO's infodemic briefing stating, \"Analysis of social networks have shown polarization for COVID-19 health topics, and this polarization is exacerbating information bottlenecks, making it difficult to ensure universal access to credible health information. Network analysis can also be enabled to identify influential users within a network, including how closely connected they are to other influential users in order to better understand the opinion of drivers on a specific issue. For COVID-19 case, social media data can help to characterize trends, the type of information spreading across platforms, and spread of information using epidemic models, as well as the diffusion of varying levels of (in)accurate information [19].\" [PERSON] et al.