‘Abba Kyari did not die of Coronavirus’: Social media and fake news during a global pandemic in Nigeria
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PROVIDER: S-EPMC9111896 | biostudies-literature | 2022 May
REPOSITORIES: biostudies-literature
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Project description:Highlights • Social media, fake news, and COVID-19.• Misinformation on social media has fuelled panic regarding the COVID-19.• Altruism is the strongest predictor of fake news sharing on COVID-19.• Socialization, information seeking and pass time predict fake news sharing.• Entertainment is not associated with sharing fake news on COVID-19. Fake news dissemination on COVID-19 has increased in recent months, and the factors that lead to the sharing of this misinformation is less well studied. Therefore, this paper describes the result of a Nigerian sample (n = 385) regarding the proliferation of fake news on COVID-19. The fake news phenomenon was studied using the Uses and Gratification framework, which was extended by an “altruism” motivation. The data were analysed with Partial Least Squares (PLS) to determine the effects of six variables on the outcome of fake news sharing. Our results showed that altruism was the most significant factor that predicted fake news sharing of COVID-19. We also found that social media users’ motivations for information sharing, socialisation, information seeking and pass time predicted the sharing of false information about COVID-19. In contrast, no significant association was found for entertainment motivation. We concluded with some theoretical and practical implications.
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Project description:One of the challenges today is to face fake news (false information) in health due to its potential impact on people's lives. This article contributes to a new application of social impact in social media (SISM) methodology. This study focuses on the social impact of the research to identify what type of health information is false and what type of information is evidence of the social impact shared in social media. The analysis of social media includes Reddit, Facebook, and Twitter. This analysis contributes to identifying how interactions in these forms of social media depend on the type of information shared. The results indicate that messages focused on fake health information are mostly aggressive, those based on evidence of social impact are respectful and transformative, and finally, deliberation contexts promoted in social media overcome false information about health. These results contribute to advancing knowledge in overcoming fake health-related news shared in social media.
| S-EPMC7177765 | biostudies-literature
Project description:The popularity of the internet, smartphones, and social networks has contributed to the proliferation of misleading information like fake news and fake reviews on news blogs, online newspapers, and e-commerce applications. Fake news has a worldwide impact and potential to change political scenarios, deceive people into increasing product sales, defaming politicians or celebrities, and misguiding visitors to stop visiting a place or country. Therefore, it is vital to find automatic methods to detect fake news online. In several past studies, the focus was the English language, but the resource-poor languages have been completely ignored because of the scarcity of labeled corpus. In this study, we investigate this issue in the Urdu language. Our contribution is threefold. First, we design an annotated corpus of Urdu news articles for the fake news detection tasks. Second, we explore three individual machine learning models to detect fake news. Third, we use five ensemble learning methods to ensemble the base-predictors' predictions to improve the fake news detection system's overall performance. Our experiment results on two Urdu news corpora show the superiority of ensemble models over individual machine learning models. Three performance metrics balanced accuracy, the area under the curve, and mean absolute error used to find that Ensemble Selection and Vote models outperform the other machine learning and ensemble learning models.
| S-EPMC7959660 | biostudies-literature
Project description:IntroductionMisinformation surrounding COVID-19 poses a global public health problem that adversely affects governments' abilities to mitigate the disease and causes accidental deaths and self-harm due to false beliefs about the virus, prevention measures, vaccines and cures. We aim to examine the relationship between exposure to and trust in COVID-19 news (from Television, social media, interpersonal communication) and information sources (healthcare experts, government, clerics) and belief in COVID-19 myths and false information, as well as critical verification practices before posting on social media.MethodsWe use a cross-sectional researcher-administered phone survey of adults living in Lebanon between March 27 and April 23, 2020.ResultsThe sample included 56.1% men and 43.9% women, 37.9% with a university degree, 63.0% older than 30, and 7% with media literacy training. Those who trust COVID-19 news from social media [95%CI:(1.05-1.52)] and interpersonal communication [95%CI:(1.25-1.82)], and those who trust information from clerics [95%CI:(1.25-1.82)] were more likely to believe in COVID-19 myths and false information. University graduates [95%CI:(0.25-0.51)] and those who trust information from government [95%CI:(0.65-0.89] were less likely to believe in myths and false information. Those who believe in COVID-19 myths and false information [95%CI:(0.25-0.70)] were less likely to engage in critical social media posting practices. Only those who underwent media literacy training [95%CI:(1.24-6.55)] were more likely to engage in critical social media posting practices.ConclusionHigher education and trust in information from government contributed to decreasing belief in COVID-19 myths and false information. Trust in news from social media, interpersonal communication and clerics contributed to increasing belief in COVID-19 myths and false information, which in turn contributed to less critical social media posting practices, thereby exacerbated the infodemic. Media literacy training contributed to increasing critical social media posting practices, thereby played a role in mitigating the infodemic.
| S-EPMC8177444 | biostudies-literature
Project description:Background: Part of the role of the media is to report any issue affecting the society to the masses. Coronavirus has become an issue of transnational concern. The importance of the media in the coverage of coronavirus disease 2019 (COVID-19) in Nigeria and its implications among Nigerian populace cannot be overestimated. This study evaluates how Nigerian media depict the coronavirus pandemic and how the depictions shape people's perception and response to the pandemic. Methods: The study employed a quantitative design (newspaper content analysis and questionnaire). The content analysis examines the nature of media coverage of coronavirus in Nigeria and China using four major national newspapers (The Sun, The Vanguard, The Guardian and The Punch). The period of study ranged from January 2020 to March 2020. A total of 1070newspaper items on coronavirus outbreak were identified across the four newspapers and content-analysed. Results: The finding shows that the coverage of the pandemic was dominated by straight news reports accounting for 763 or (71.3%) of all analysed items. This was followed by opinions 169(15.8%), features 120 (11.2%) and editorials 18 (1.7%) respectively. The Punch 309 (28.9%)reported the outbreak more frequently than The Sun 266 (24.9%), The Guardian 258 (24.1%), and Vanguard 237 (22.1%). Finding further suggests that the framing pattern adopted by the newspapers helped Nigerians to take precautionary measures. Conclusion: Continuous reportage of COVID-19 has proved effective in creating awareness about safety and preventive measures thereby helping to 'flatten the curve' and contain the spread of the virus. However, the newspapers should avoid creating fear/panic in reporting the pandemic.
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Project description:Sharing of fake news on social media platforms is a global concern, with research offering little insight into the motives behind such sharing. This study adopts a mixed-method approach to explore fake-news sharing behaviour. To begin with, qualitative data from 58 open-ended essays was analysed to identify six behavioural manifestations associated with sharing fake news. Thereafter, research model hypothesizing the association between these behaviours was proposed using the honeycomb framework and the third-person effect hypothesis. Age and gender were the control variables. Two data sets obtained from cross-sectional surveys with 471 and 374 social media users were utilized to test the proposed model. The study results suggest that instantaneous sharing of news for creating awareness had positive effect on sharing fake news due to lack of time and religiosity. However, authenticating news before sharing had no effect on sharing fake news due to lack of time and religiosity. The study results also suggest that social media users who engage in active corrective action are unlikely to share fake news due to lack of time. These results have significant theoretical and practical implications.
| S-EPMC7340407 | biostudies-literature
Project description:To investigate how people assess whether politically consistent news is real or fake, two studies (N = 1,008; N = 1,397) with adult American participants conducted in 2020 and 2022 utilized a within-subjects experimental design to investigate perceptions of news accuracy. When a mock Facebook post with either fake (Study 1) or real (Study 2) news content was attributed to an alternative (vs. a mainstream) news outlet, it was, on average, perceived to be less accurate. Those with beliefs reflecting News Media Literacy demonstrated greater sensitivity to the outlet's status. This relationship was itself contingent on the strength of the participant's partisan identity. Strong partisans high in News Media Literacy defended the accuracy of politically consistent content, even while recognizing that an outlet was unfamiliar. These results highlight the fundamental importance of looking at the interaction between user-traits and features of social media news posts when examining learning from political news on social media.
| S-EPMC10562704 | biostudies-literature
Project description:Fake news is a real problem in today's world, and it has become more extensive and harder to identify. A major challenge in fake news detection is to detect it in the early phase. Another challenge in fake news detection is the unavailability or the shortage of labelled data for training the detection models. We propose a novel fake news detection framework that can address these challenges. Our proposed framework exploits the information from the news articles and the social contexts to detect fake news. The proposed model is based on a Transformer architecture, which has two parts: the encoder part to learn useful representations from the fake news data and the decoder part that predicts the future behaviour based on past observations. We also incorporate many features from the news content and social contexts into our model to help us classify the news better. In addition, we propose an effective labelling technique to address the label shortage problem. Experimental results on real-world data show that our model can detect fake news with higher accuracy within a few minutes after it propagates (early detection) than the baselines.
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Project description:Older adults are especially susceptible to fake news online, possibly because they are less digitally literate compared to younger individuals. Interventions for older adults have emerged to improve digital literacy, although there has been little evaluation of their effectiveness in improving older adults' resilience to fake news. We report the results of a digital literacy intervention for older adults administered during the 2020 U.S. election. The intervention was a 1-hour, self-directed series of interactive modules designed to teach concepts and skills for identifying misinformation online. Consistent with our pre-registered hypothesis, older adults (Mage = 67) in the treatment condition (N = 143) significantly improved their likelihood of accurately discerning fake from true news from 64% pre-intervention to 85% post-intervention. In contrast, older adults in the control condition (N = 238) did not significantly improve (from 55% to 57%). The treated older adults were also more likely to employ strategies for identifying misinformation online compared to pre-intervention and the control group.
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