What have researchers learned about the impact of Misinformation about covid 19 on social media

Comparison and Contrast: What Have Researchers Learned about the Impact of Misinformation about COVID-19 on social media?

COVID-19 on social media?

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What articles have similarities in each section below?

a. Methodology

Apuke & Omar (2021) used surveys where data was drawn from 385 social media users. Similar to Lee et al. (2023), which used systematic empirical quantitative research with a sample size of 1363 social media users.

b. Findings

The studies showed that social media platforms significantly impacted the sharing of scientific data about the covid-19 pandemic. Misinformation led to people practising wrong containment measures and being afraid of taking the vaccines because of the fears instilled by social media users. 33% of the people who rejected the vaccines were misinformed in social media that the components of the vaccines could affect their DNA, affecting their health in the long run. The research further showed that the contradicting information made the people lose a sense of direction, jeopardizing the fight against the virus. 77% of the people using social media can access different forms of information on social media platforms (Ngai et al., 2022).

In comparison, findings from Tasnim et al., (2020) indicated that 27% of respondents proved that the information was helpful and helped them to make the right choices. On the contrary, 66% of the respondents reported that the information contained misinformation and fake news that inflicted more fear on the people and increased their vulnerability to other diseases (Tasnim et al., 2020). Both studies underscored how the misinformation on social media platforms negatively impacted and jeopardized the fight against the pandemic.

c. Recommendations

Apuke & Omar (2021) and Lee et al. (2023) recommended that the managed social media platforms and ads that present healthcare information will also be shared via reasonable means. Likewise, Tasnim et al. (2020) recommended forming credible healthcare services' social media platforms to ensure all information is shared from a credible source. Ngai et al. (2022) stated that it only takes credible sources to share vaccine information. It recommended filtering information before being released to the public domain. All the studies were keen on obtaining information before being released for public use.

1. What articles have differences in each section below?

a. Methodology

Apuke & Omar (2021) and Lee et al. (2023) used surveys for research to collect data from 385 and 1363 participants, respectively. However, Ngai et al. (2022) used a database to observe the misinformation about vaccination news and how it could be used to make better decisions. Tasnin et al. (2020), on the other hand, used qualitative data analysis to determine the outcome of social media.

b. Findings

Apuke & Omar (2021) showed that although many people were using social media, not all were affected by the misinformation, meaning that people could choose between what to believe and what to ignore from the social media platforms. However, the findings differed from the information from Ngai et al. (2022), which proved misinformation regarding vaccination information. Rumours were more easily believed among uneducated users than by educated users. Therefore, the variables proved that education level was critical in understanding misinformation and theories. The key difference in the findings was therefore made possible because of the differences in the impacts of the misinformation.

c. Recommendations

Ngai et al. (2022) recommend additional research on how the level of education affects people on social media and how they are affected by the information. The selection of variables is an essential factor in research supporting better outcomes. Research by Tasnin et al. (2020) further recommends advertisements to underscore the importance of collecting reading from authenticated and verified posts. Rumours find their way to the people to ensure better outcomes in the discourse. Apuke & Omar (2021) somewhat differed from Ngai et al. (2022) recommendation because one study focused on the importance of education, and the other underscored authentication of the data posted on social media.

References

Apuke, O. D., & Omar, B. (2021). Social media affordances and information abundance: Enabling fake news sharing during the COVID-19 health crisis.  Health Informatics Journal,  27(3), 14604582211021470. https://doi.org/10.1177/14604582211021470

Lee, S., Tandoc Jr, E. C., & Lee, E. W. (2023). Social media may hinder learning about science; social media's role in learning about COVID-19.  Computers in Human Behavior,  138(1), 107487. https://doi.org/10.1016/j.chb.2022.107487

Ngai, C. S. B., Singh, R. G., & Yao, L. (2022). Impact of COVID-19 vaccine misinformation on social media virality: a content analysis of message themes and writing strategies. Journal of medical Internet research,  24(7), e37806. https://doi.org/10.2196/37806

Tasnim, S., Hossain, M. M., & Mazumder, H. (2020). Impact of rumours and misinformation on COVID-19 in social media. Journal of preventive medicine and public health,  53(3), 171-174. https://doi.org/10.3961%2Fjpmph.20.094