Diffusion of COVID-19 Misinformation in Kenyan X Conversations
DOI:
https://doi.org/10.47604/ijcpr.3166Keywords:
COVID-19, Diffusion, Misinformation, Hashtags, Rumor, Social MediaAbstract
Purpose: The study set out to explore the role of X conversations in the spread of misinformation about the COVID-19 pandemic in Kenya.
Methodology: The study was guided by the Rumor Theory. The study adopted a descriptive survey design which allowed the researchers to collect data without interacting with participants. Data was collected from existing online records of conversations on X and other relevant websites such as the Ministry of Health. The data was sourced from hashtags and tweets related to the COVID-19 pandemic in Kenya, posted in the period from March 2020 to April 2021. The hashtags and tweets were mined using the free API tool for geolocated tweets. 16 hashtags and 200 tweets were selected for the study. Quantitative data was analyzed using descriptive statistics while qualitative data was analyzed using content analysis under classified themes.
Findings: The findings of the study indicate that none of the hashtags created by Kenyans was framed to spread misinformation but the tweets under the different hashtags analyzed contained misinformation. Findings also indicate that verified X handles were involved in either creating or spreading COVID-19 misinformation. Additionally, false claims were found to diffuse faster than partially false claims as observed in the tweets with misinformation. Compared to a background corpus of COVID-19 tweets, tweets with misinformation were more often concerned with discrediting other information on social media.
Unique Contribution to Theory, Practice and Policy: We recommend that the government and stakeholders in health ought to counter COVID-19 misinformation online, and equip users with basic digital literacy skills regarding consumption of online information while continuously monitoring online discourses. A policy on online health communication needs to be developed and implemented.
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