Accuracy of health‐related information regarding COVID‐19 on Twitter during a global pandemic

Swetland, Sarah B.; Rothrock, Ava N.; Andris, Halle; Davis, Bennett; Nguyen, Linh; Davis, Phil; Rothrock, Steven G.

doi:10.1002/wmh3.468

Cited by 18 publications

(36 citation statements)

References 36 publications

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“…There were a number of studies that identified misinformation that had the potential to cause danger to people's health and well-being [42,44,46,47,49,50,55,57]. One study, based on data from Massachusetts and Rhode Island, concluded that there was a 34.4% increase in calls to regional poison control centers compared to the previous 8-year period [42].…”

Section: Subtheme 11: Potential Harms To the Individualmentioning

confidence: 99%

Complementary, Alternative, and Integrative Medicine-Specific COVID-19 Misinformation on Social Media: A Scoping Review

Ng¹,

Liu²,

Maini³

et al. 2023

Preprint

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Background: The sharing of health-related information has become increasingly popular on social media. Unregulated information sharing has led to the spread of misinformation, especially regarding complementary, alternative, and integrative medicine (CAIM). This scoping review synthesized evidence surrounding the spread of CAIM-related misinformation on social media during the COVID-19 pandemic.Methods: This review was informed by a modified version of the Arksey and O’Malley scoping review framework. AMED, EMBASE, PsycINFO and MEDLINE databases were searched systematically from inception to January 2022. Eligible articles explored COVID-19 misinformation on social media and contained sufficient information on CAIM therapies. Common themes were identified using an inductive thematic analysis approach.Results: Twenty-eight articles were included. The following themes were synthesized: 1) misinformation prompts unsafe and harmful behaviours, 2) misinformation can be separated into different categories, 3) individuals are capable of identifying and refuting CAIM misinformation, 4) non-representative study samples have resulted in considerable generalizability issues, and 5) studies argue governments and social media companies have a responsibility to resolve the spread of COVID-19 misinformation.Conclusions: Misinformation can spread more easily when shared on social media. Our review suggests that misinformation about COVID-19 related to CAIM that is disseminated online contributes to unsafe health behaviours, however, this may be remedied via public education initiatives and stricter media guidelines. The results of this scoping review are crucial to understanding the behavioural impacts of the spread of COVID-19 misinformation about CAIM therapies, and can inform the development of public health policies to mitigate these issues.

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Section: Subtheme 11: Potential Harms To the Individualmentioning

confidence: 99%

Complementary, Alternative, and Integrative Medicine-Specific COVID-19 Misinformation on Social Media: A Scoping Review

Ng¹,

Liu²,

Maini³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Misinformation based on the Internet and social media remain a common and significant problem during the pandemic. The findings suggest unverified accounts contain more erroneous medical information than verified ones [ 46 ]. Therefore, it is still necessary for us to consider the influence of unverified bot accounts and proceed through bot detection tools.…”

Section: Literature Reviewmentioning

confidence: 99%

Public Opinion Manipulation on Social Media: Social Network Analysis of Twitter Bots during the COVID-19 Pandemic

Weng

Lin

2022

IJERPH

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Social media is not only an essential platform for the dissemination of public health-related information, but also an important channel for people to communicate during the COVID-19 pandemic. However, social bots can interfere with the social media topics that humans follow. We analyzed and visualized Twitter data during the prevalence of the Wuhan lab leak theory and discovered that 29% of the accounts participating in the discussion were social bots. We found evidence that social bots play an essential mediating role in communication networks. Although human accounts have a more direct influence on the information diffusion network, social bots have a more indirect influence. Unverified social bot accounts retweet more, and through multiple levels of diffusion, humans are vulnerable to messages manipulated by bots, driving the spread of unverified messages across social media. These findings show that limiting the use of social bots might be an effective method to minimize the spread of conspiracy theories and hate speech online.

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“…26 discovered the issues, discrepancies, and sentiments of COVID-19 Twitter data using Valence Aware Dictionary and Sentiment Reasoner (VADER). 27 performed accuracy check on information about health in Twitter data during COVID-19 using Botometer. 28 classified sentiments about COVID-19 vaccination, between January and October 2020 using 31, 100 tweets from Autralian users.…”

Section: Related Workmentioning

confidence: 99%

Reliable Knowledge Discovery from Social Media Data in Health Crisis in Developing Countries

Naseem¹,

Hassan²,

Naseer³

et al. 2022

Preprint

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Social media is a barometer to anticipate sentiment of the public about the state of affairs and ongoing pandemic engaged an additional user base who are confined to their stations. COVID-19 startled the world and the crisis exacerbates in the absence of sufficient data for policy making. The data from social media and a timely analysis can provide sufficient statistics for decision-making. This study explores Twitter data to discover knowledgeable statistics on public sentiments about COVID-19 vaccination in developing countries. The study inspects data collected from two extremely populated developing countries: India and Pakistan. Support Vector Machine (SVM) classifier achieves 74.3% accuracy on the manually labeled dataset. Furthermore, the sentiment analysis is correlated with other indigenous factors like regional literacy rate and COVID-19 calamities in the time interval. It is observed that the negative to positive sentiments correlates with a lower to higher regional literacy rate and a higher COVID-19 intensity causes positive sentiments towards vaccination. The correlations of results with indigenous factors may help to advocate the devised strategies to the right audience and social media knowledge discovery with machine learning techniques may help to recover from data scarcity challenges in a medical emergency like COVID-19 in developing countries. Please note: Abbreviations should be introduced at the first mention in the main text – no abbreviations lists. Suggested structure of main text (not enforced) is provided below.

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Accuracy of health‐related information regarding COVID‐19 on Twitter during a global pandemic

Cited by 18 publications

References 36 publications

Complementary, Alternative, and Integrative Medicine-Specific COVID-19 Misinformation on Social Media: A Scoping Review

Complementary, Alternative, and Integrative Medicine-Specific COVID-19 Misinformation on Social Media: A Scoping Review

Public Opinion Manipulation on Social Media: Social Network Analysis of Twitter Bots during the COVID-19 Pandemic

Reliable Knowledge Discovery from Social Media Data in Health Crisis in Developing Countries

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