Misinformation about COVID-19 and Venezuelan Migration: Trends in Twitter Conversation during a Pandemic

Donato, Katharine M.; Singh, Lisa; Arab, Ali; Jacobs, Elizabeth; Post, Douglas M.

doi:10.1162/99608f92.a4d9a7c7

Cited by 6 publications

(5 citation statements)

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“…Together with publication in traditional media about reliable sources of information or the publication of media reports about sources of misinformation [60][61][62][63], popular culture is proving to be effective. Engaging films, TV shows, and games can transport people to alternative visions and help to expand the sense of the possible towards a much-needed change [64].…”

Section: Discussionmentioning

confidence: 99%

Misinformation and Its Impact on Contested Policy Issues: The Example of Migration Discourses

Komendantova,

Erokhin,

Albano

2023

Societies

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Misinformation, in the form of false or inaccurate information deliberately created and spread through various channels, including social media, has become pervasive in the context of migration. An analysis of 45,000 English tweets revealed a wide range of attitudes towards migrants, including the presence of misinformation, concerns, and positive and negative attitudes. This study acknowledges the negative effects of misinformation, such as the formation of preconditions that promote false representations of migrants, foster negative attitudes, and consolidate prejudices against them. Misinformation also leads to mistrust among migrants towards official authorities and creates an environment conducive to exploitation by smugglers and traffickers. To address these issues, this study suggests corrective measures, including raising awareness, promoting evidence-based reasoning, and facilitating diverse forms of interpersonal dialogue.

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Section: Discussionmentioning

confidence: 99%

Misinformation and Its Impact on Contested Policy Issues: The Example of Migration Discourses

Komendantova,

Erokhin,

Albano

2023

Societies

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“…We discovered that participants were exposed to a spread of misinformation, most of which came from social media and non-secular institutions. 28 , 29 , 31 , 44 This resulted in confusion, distress, and mistrust in participants’ daily lives about the COVID-19 vaccine. Vaccine refusal could be attributed to three factors: safety concerns, negative stories, and private knowledge, all of which had been exacerbated by recent exposure to misinformation via various platforms.…”

Section: Discussionmentioning

confidence: 99%

“…Data were gathered by face-to-face interviews with the use of a standardized questionnaire developed from literature. 5 , 13 , 14 , 22 , 28 , 40 , 42 , 43 The dependent variable was refusal to undergo COVID-19 immunization, while the independent variables were socio-demographic characteristics, technical factors like eHealth literacy, source of COVID-19 information, frequency of internet use and computer literacy.…”

Section: Methodsmentioning

confidence: 99%

“…Controversies over vaccine safety, which are widely publicized in news headlines, talk programs, and popular publications, also increase vaccine hesitation and anti-vaccination behavior in the community. 14,[28][29][30][31][32] According to several studies, the heart of anti-vaccine views is a conspiracy notion that vaccinations do not function and/or are actively harmful because they cause many defects to the people who took the vaccine. 6,[33][34][35] Some people's resistance to vaccinations also stems from theological arguments.…”

Section: Introductionmentioning

confidence: 99%

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Myth and Misinformation on COVID-19 Vaccine: The Possible Impact on Vaccination Refusal Among People of Northeast Ethiopia: A Community-Based Research

Kalayou¹,

Awol²

2022

RMHP

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Background To prevent the spread of COVID-19 and carry out a successful vaccination program especially in low-income countries, people must have faith on scientists and health experts. The most significant challenge to vaccination programs’ efficacy is now regarded to be a lack of information and trust in immunization due to myths and misinformation spread in the community. Therefore, this study aimed to identify the myth and misconceptions that are propagated about the COVID-19 vaccine, the refusal rate of the vaccine and determine the factors associated with COVID-19 vaccine refusal. Methods A community-based cross-sectional study was conducted from December 7 to January 25, 2022. Face-to-face interviews with a standardized questionnaire were used to collect data on the variables. Data were entered into the statistical tool Epi data version 3.1 and then exported to SPSS version 25 for analysis. Binary logistic regression, both bivariable and multivariable, was conducted. In the multivariable binary logistic regression model, the adjusted odds ratio with 95% confidence interval was used to declare statistically significant factors based on a p value less than 0.05. Results Out of the total 574 respondents, 60.3% [95% CI (55.5, 64.2)] of them refused to take COVID-19 vaccine. In this study, respondent’s age [AOR = 2.1 at 95% CI: (1.8, 4.9)], perception on COVID-19 vaccine [AOR = 3.0 at 95 CI: (1.9, 4.6)], eHealth literacy [AOR = 2.7 at 95% CI: (1.7, 4.1)], source of information about the vaccine [AOR = 2.9 at 95% CI: (1.9, 4.4)], computer literacy [AOR = 2.8 at 95 CI: (1.8, 4.2)] and frequency of internet use [AOR = 2.2 at 95 CI: (1.8, 5.3)] were identified as determinant factors for COVID-19 vaccine acceptance. Conclusion Factors like eHealth literacy, source of information about the vaccine, frequency of internet use, respondent’s perception about the vaccine and computer literacy were found to be determinant factors for COVID-19 vaccine acceptance.

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“…Social bots also attempt to influence the online conversation, possibly making it seem as if conditions are different from reality. To further exacerbate the problem, a great deal of misinformation is spreading in social media from both people and bots (Donato et al, 2021). However, if people believe and act upon the information they obtain from these sources, they may turn out to be very good indicators as to the drivers that contribute towards movements.…”

Section: Constructing Variables From Big Datamentioning

confidence: 99%

Environmental change and human mobility: Opportunities and challenges of big data

Martin

Singh

2022

International Migration

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This paper explores the use of big data in understanding population movements in the context of environmental change, with particular attention to publicly available information from social media and newspapers. After discussing causal factors, the paper discusses the benefits and challenges of using big data, and mathematical models that may help capture the complexity of human mobility in the context of environmental change. We conclude that big data can be an important part of a toolkit in discerning drivers of migration and displacement. It is no panacea, however; the paper discusses potential problems in its use, particularly if big data are analysed to prevent people from moving out of harm's way. Therefore, partnerships between computer scientists and subject matter experts and practitioners are essential to ensuring that what is gathered from big data is usable, credible, and protects the privacy and rights of those who may be displaced.

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Misinformation about COVID-19 and Venezuelan Migration: Trends in Twitter Conversation during a Pandemic

Cited by 6 publications

References 0 publications

Misinformation and Its Impact on Contested Policy Issues: The Example of Migration Discourses

Misinformation and Its Impact on Contested Policy Issues: The Example of Migration Discourses

Myth and Misinformation on COVID-19 Vaccine: The Possible Impact on Vaccination Refusal Among People of Northeast Ethiopia: A Community-Based Research

Environmental change and human mobility: Opportunities and challenges of big data

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