#COVID-19 Misinformation: Saudi Arabia as a Use Case

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FinalASIS&T Poster presentation.pdf (7.64 MB)
Submission to ASIS&T - Final Draft .pdf (184.86 KB)

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https://zenodo.org/record/3932081#.Yp5muqjMKUk

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https://doi.org/10.5281/zenodo.3932081
 http://hdl.handle.net/11603/24881

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UMBC Information Systems Department
UMBC Student Collection

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https://orcid.org/0000-0002-2486-5979
 https://orcid.org/0000-0001-6164-6620

Date

2020-06-09

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presentations (communicative events)
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Abstract

In this research, we aim to gain deep insights into information behavior when discussing epidemics on Twitter. We are more specifically interested in identifying misinformation spread regarding epidemics around the world and in particular, in Saudi Arabia. We are also interested in understanding the effects of governmental laws as a way to prevent the spread of misinformation. Questions to be answered include: Which types of misinformation spread the most in pandemics? How does misinformation evolve over time? What is the effect of governmental laws in the spread of misinformation? We propose a mixed method study to determine if information-exchanging behaviors can be used to minimize the effects of emergent misinformation. To do this, Twitter data was collected for the period beginning in December 2019 to the present day of April 10, 2020 using several keywords related to the pandemic in Arabic. In addition to twitter data, we also created a short survey to collect rumors and fake news that spread in the community. To study the effect of governmental Saudi laws in the spread of misinformation, the misinformation laws were collected.