Fake news and COVID 19: modelling the predictors of fake news sharing among social media users
From Digital Culture & Society
Contents |
[edit] Fake news and COVID 19: modelling the predictors of fake news sharing among social media users
Apuke, O. D., & Omar, B. (2021). Fake news and COVID-19: modelling the predictors of fake news sharing among social media users. Telematics and Informatics, 56, 101475–101475.
https://doi.org/10.1016/j.tele.2020.101475]
[edit] Context
The Apuke & Omar article discusses fake news sharing on social media in relation to Covid-19. There have been many studies done on Covid-19 fake news sharing in first world countries like the USA or the UK, which is why this article looked into how this differs for a developing country, like Nigeria. The authors decipher what factors lead to sharing misinformation online. The Apuke & Omar article looks at an under explored area of this topic, why fake news and misinformation is spread online, and what the behavioural motivations/intentions are behind the action of spreading fake news. This is an important factor to consider when looking at the spread of fake news on social media, to really understand why it happens and how to deal with it.
[edit] Overview
Before diving into their own study and survey, the authors summarize how fake news has affected social media, specifically in relation to Covid-19. They discuss the effects that this specifically had on the Nigerian population and how fake news has warped some Nigerians' understanding and trust of Covid-19 information. Apuke & Omar used seven different areas to try and predict fake news sharing behaviours: altruism, information sharing, information seeking, socialism, entertainment, pass time, and fake news sharing. They discussed each of these areas in detail and why they had the potential to be a behavior that affected the sharing of fake news. When collecting their data, Apuke & Omar put out a Google form survey on social media and respondents were to fill out the survey and share it with others in their network, to gain a large enough sample size. Through the analysis of the data that came from this survey, Apuke & Omar concluded that altruism was the strongest predictor of fake news sharing when it came to Covid-19. They were shocked to discover the fact that entertainment had no relationship with the sharing of Covid-19 fake news online.
[edit] Strengths and Weaknesses
The major strength of the Apuke & Omar article is the fact that it demonstrated what factors or behaviours were predictors of fake news spreading on social media, specifically when it comes to Covid-19. The article focused on why specifically, fake news is shared on social media, and ranked the factors on a scale of most relevant to least relevant. It is important to understand why the behaviour is happening in order to deal with the behaviour, and learn how to be better equipped when people are faced with fake news in their digital media diets. This is an under explored area of Covid-19 fake news, so this study aids in understanding an area society has inadequate knowledge about. Any research that has been done in this area has been done on Western countries, which is why this study chose to cover samples from Nigeria, as it has gained little research in this area. This is very important, as the threat of fake news on social media surrounding the pandemic has become concerning, so it is important to be able to predict these behaviours.
A major weakness or limitation of the Apuke & Omar article was the fact that it was conducted in Nigeria alone. The major factors that they found contributed to the spread of fake news on social media was altruism. This was also named as a common cultural trait for people of Nigeria. Therefore, it is hard to tell if these results would be the same globally, or in more influential, first world countries. Another weakness of this study was the way they chose their sample population. They simply advertised this survey on social media in Nigeria, and asked those who completed it to extend it to their network, to gain more people. This can result in a biased sample size, having people from all one demographic who would answer these questions similarly, and therefore skew the results of the study.
[edit] Assessment
This Apuke & Omar article conducts a great analysis of the factors that predict why people spread fake news on social media. The article discusses the problems that come with fake news being spread on social media, and specifically analyzed the seven factors that were seen as possible predictors for this behaviour. This article would be very helpful and insightful for audiences who are looking to learn why fake news is spread and predictable characteristics of those sharing fake news. It allowed for first hand data collection, and specific findings on which of the factors were most-least important when considering why fake news is shared on social media. Future studies should be completed in other/different countries, or even globally to see how the results differ based on the location and norms of the country’s culture.
Sb19qp 12:49, 9 December 2023 (EST)
Please consider the environment before
printing this page.