Twitter and Facebook posts about COVID-19 are less likely to spread misinformation compared to other health topics

Correction: Twitter and Facebook posts about COVID-19 are less likely to spread misinformation compared to other health topics

[This corrects the article DOI: 10.1371/journal.pone.0261768.].

Assessment of the Early Detection of Anosmia and Ageusia Symptoms in COVID-19 on Twitter: Retrospective Study

BACKGROUND

During the unprecedented COVID-19 pandemic, social media has been extensively used to amplify the spread of information and to express personal health-related experiences regarding symptoms, including anosmia and ageusia, 2 symptoms that have been reported later than other symptoms.

OBJECTIVE

Our objective is to investigate to what extent Twitter users reported anosmia and ageusia symptoms in their tweets and if they connected them to COVID-19, to evaluate whether these symptoms could have been identified as COVID-19 symptoms earlier using Twitter rather than the official notice.

METHODS

We collected French tweets posted between January 1, 2020, and March 31, 2020, containing anosmia- or ageusia-related keywords. Symptoms were detected using fuzzy matching. The analysis consisted of 3 parts. First, we compared the coverage of anosmia and ageusia symptoms in Twitter and in traditional media to determine if the association between COVID-19 and anosmia or ageusia could have been identified earlier through Twitter. Second, we conducted a manual analysis of anosmia- and ageusia-related tweets to obtain quantitative and qualitative insights regarding their nature and to assess when the first associations between COVID-19 and these symptoms were established. We randomly annotated tweets from 2 periods: the early stage and the rapid spread stage of the epidemic. For each tweet, each symptom was annotated regarding 3 modalities: symptom (yes or no), associated with COVID-19 (yes, no, or unknown), and whether it was experienced by someone (yes, no, or unknown). Third, to evaluate if there was a global increase of tweets mentioning anosmia or ageusia in early 2020, corresponding to the beginning of the COVID-19 epidemic, we compared the tweets reporting experienced anosmia or ageusia between the first periods of 2019 and 2020.

RESULTS

In total, 832 (respectively 12,544) tweets containing anosmia (respectively ageusia) related keywords were extracted over the analysis period in 2020. The comparison to traditional media showed a strong correlation without any lag, which suggests an important reactivity of Twitter but no earlier detection on Twitter. The annotation of tweets from 2020 showed that tweets correlating anosmia or ageusia with COVID-19 could be found a few days before the official announcement. However, no association could be found during the first stage of the pandemic. Information about the temporality of symptoms and the psychological impact of these symptoms could be found in the tweets. The comparison between early 2020 and early 2019 showed no difference regarding the volumes of tweets.

CONCLUSIONS

Based on our analysis of French tweets, associations between COVID-19 and anosmia or ageusia by web users could have been found on Twitter just a few days before the official announcement but not during the early stage of the pandemic. Patients share qualitative information on Twitter regarding anosmia or ageusia symptoms that could be of interest for future analyses.

The efficacy of Facebook's vaccine misinformation policies and architecture during the COVID-19 pandemic

Online misinformation promotes distrust in science, undermines public health, and may drive civil unrest. During the coronavirus disease 2019 pandemic, Facebook-the world's largest social media company-began to remove vaccine misinformation as a matter of policy. We evaluated the efficacy of these policies using a comparative interrupted time-series design. We found that Facebook removed some antivaccine content, but we did not observe decreases in overall engagement with antivaccine content. Provaccine content was also removed, and antivaccine content became more misinformative, more politically polarized, and more likely to be seen in users' newsfeeds. We explain these findings as a consequence of Facebook's system architecture, which provides substantial flexibility to motivated users who wish to disseminate misinformation through multiple channels. Facebook's architecture may therefore afford antivaccine content producers several means to circumvent the intent of misinformation removal policies.

High level of correspondence across different news domain quality rating sets

One widely used approach for quantifying misinformation consumption and sharing is to evaluate the quality of the news domains that a user interacts with. However, different media organizations and fact-checkers have produced different sets of news domain quality ratings, raising questions about the reliability of these ratings. In this study, we compared six sets of expert ratings and found that they generally correlated highly with one another. We then created a comprehensive set of domain ratings for use by the research community (github.com/hauselin/domain-quality-ratings), leveraging an ensemble "wisdom of experts" approach. To do so, we performed imputation together with principal component analysis to generate a set of aggregate ratings. The resulting rating set comprises 11,520 domains-the most extensive coverage to date-and correlates well with other rating sets that have more limited coverage. Together, these results suggest that experts generally agree on the relative quality of news domains, and the aggregate ratings that we generate offer a powerful research tool for evaluating the quality of news consumed or shared and the efficacy of misinformation interventions.

Media Consumption and COVID-19-Related Precautionary Behaviors During the Early Pandemic: Survey Study of Older Adults

BACKGROUND

During the COVID-19 pandemic, media sources dedicated significant time and resources to improve knowledge of COVID-19 precautionary behaviors (eg, wearing a mask). Many older adults report using the television, radio, print newspapers, or web-based sources to get information on political news, yet little is known about whether consuming news in the early phase of the pandemic led to behavior change, particularly in older adults.

OBJECTIVE

The goals of this study were to determine (1) whether dosage of news consumption on the COVID-19 pandemic was associated with COVID-19 precautionary behaviors; (2) whether being an ever-user of social media was associated with engagement in COVID-19 precautionary behaviors; and (3) among social media users, whether change in social media use during the early stages of the pandemic was associated with engagement in COVID-19 precautionary behaviors.

METHODS

Data were obtained from a University of Florida-administered study conducted in May and June of 2020. Linear regression models were used to assess the association between traditional news and social media use on COVID-19 precautionary behaviors (eg, mask wearing, hand washing, and social distancing behaviors). Analyses were adjusted for demographic characteristics, including age, sex, marital status, and education level.

RESULTS

In a sample of 1082 older adults (mean age 73, IQR 68-78 years; 615/1082, 56.8% female), reporting 0 and <1 hour per day of media consumption, relative to >3 hours per day, was associated with lower engagement in COVID-19 precautionary behaviors in models adjusted for demographic characteristics (β=-2.00; P<.001 and β=-.41; P=.01, respectively). In addition, increasing social media use (relative to unchanged use) was associated with engagement in more COVID-19 precautionary behaviors (β=.70, P<.001). No associations were found between being an ever-user of social media and engaging in COVID-19 precautionary behaviors.

CONCLUSIONS

The results demonstrated an association between higher media consumption and greater engagement in COVID-19 precautionary behaviors in older adults. These findings suggest that media can be effectively used as a public health tool for communication of prevention strategies and best practices during future health threats, even among populations who are historically less engaged in certain types of media.

[Development of the INSABI educational strategy: a lesson learned from the COVID-19 epidemic]

The Institute for Health for Well-being (INSABI according to its initials in Spanish), in collaboration with the National Institute of Medical Sciences and Nutrition Salvador Zubirán (INCMNSZ), instituted the Continuous Training on clinical management "Mexico against COVID-19" in 2020, with the purpose of training the frontline health personnel in the care for patients with COVID-19 in the context of hospital reconversion through the COVIDUTI platform. Virtual conferences were held for medical personnel from all over the country with the possibility of interacting with various specialists. In 2020, 215 sessions were held and 158 in 2021. That year educational content was expanded and included topics for other health categories, such as nursing and social work. In October 2021, it was established the Health Educational System for Well-being (SIESABI), with the aim of promoting continuous and permanent education for health workers. It currently offers face-to-face and virtual courses, permanent seminars, and telementoring, with the possibility of providing academic follow-up to its subscribers and linking priority courses that are on other platforms. The educational platform is an opportunity to unify the efforts of the health system in Mexico in the continuous and permanent education of professionals who care for people without social security and thereby contribute to the implementation of a model of care based on primary health care (PHC).

Older adults' exposure to and posting of health-related messages on Facebook by chronic health condition status

Objective

Older adults may be particularly interested in health-related content on Facebook, especially those who have chronic health conditions. The purpose of this study was to compare older adult Facebook users with and without a chronic health condition on their frequency of posting and exposure to health-related content.

Methods

Participants, recruited via Qualtrics, were regular Facebook users aged 50 + years. Participants were asked separately if they had seen, posted, and shared: Health-related information; about others'/their own health behaviors (e.g., exercise); and about others'/their own medical condition. Six logistic regression models, controlling for demographics and Facebook login frequency, were run to assess whether viewing and/or posting health-related messages differed by chronic health condition status.

Results

Respondents (N = 697; 77.9% female) were on average 61.2 (SD = 7.9) years old and (n = 625; 89.7%) were White. One-half reported a chronic health condition (n = 351; 50.4%). In adjusted models, those with a chronic health condition had a higher likelihood of seeing posts containing health information (OR = 1.41; 95% CI: 1.04, 1.93) and about others' medical conditions (OR = 1.67; 95% CI: 1.22, 2.27) at least once a month compared to those with no chronic health conditions. People with and without chronic health conditions did not differ in terms of how often they see others' post about health behaviors. Those with a chronic health condition had a higher likelihood of posting or sharing health information (OR = 1.67; 95% CI: 1.22, 2.27), posting about their own health behaviors (OR = 1.55; 95% CI: 1.00, 2.44; p = 0.048), and about their health condition (OR = 1.96; 95% CI: 1.17, 3.27) at least once a month.

Conclusion

Most older adults on Facebook are exposed to and post multiple forms of health-related content. Therefore, Facebook may be an appropriate channel for conducting health-related communication targeting older adults.

Breast cancer prevention and treatment misinformation on Twitter: An analysis of two languages

Objective

To determine the prevalence and types of misinformation on Twitter related to breast cancer prevention and treatment; and compare the differences between the misinformation in English and Malay tweets.

Methods

A total of 6221 tweets related to breast cancer posted between 2018 and 2022 were collected. An oncologist and two pharmacists coded the tweets to differentiate between true information and misinformation, and to analyse the misinformation content. Binary logistic regression was conducted to identify determinants of misinformation.

Results

There were 780 tweets related to breast cancer prevention and treatment, and 456 (58.5%) contain misinformation, with significantly more misinformation in Malay compared to English tweets (OR = 6.18, 95% CI: 3.45-11.07, p < 0.001). Other determinants of misinformation were tweets posted by product sellers and posted before the COVID-19 pandemic. Less misinformation was associated with tweets utilising official/peer-reviewed sources of information compared to tweets without external sources and those that utilised less reliable information sources. The top three most common content of misinformation were food and lifestyle, alternative medicine and supplements, comprising exaggerated claims of anti-cancer properties of traditional and natural-based products.

Conclusion

Misinformation on breast cancer prevention and treatment is prevalent on social media, with significantly more misinformation in Malay compared to English tweets. Our results highlighted that patients need to be educated on digital health literacy, with emphasis on utilising reliable sources of information and being cautious of any promotional materials that may contain misleading information. More studies need to be conducted in other languages to address the disparity in misinformation.

Tackling the COVID-19 infodemic among Syrian refugees in Lebanon: Development and evaluation of the "Wikaytek" tool

Objective

The COVID-19 infodemic has been a global public health challenge, especially affecting vulnerable populations such as Syrian refugees with limited internet access and functional, health, digital, and media literacies. To address this problem, we developed Wikaytek, a software to diffuse reliable COVID-19 information using WhatsApp, the preferred communication channel among Syrian refugees. In this paper, we describe the systematic development of the tool.

Methods

We undertook a pilot study guided by the Humanitarian Engineering Initiative (HEI)'s user-centered design framework, comprising five stages: (a) user research, including needs assessment and desk review of interventions with target users; (b) concept design based on platform and source selection, message format, concept testing, and architecture design; (c) prototyping and implementation, encompassing software development and system operation; (d) user testing (alpha and beta); and (e) evaluation through software analytics and user interviews. We reported a qualitative process evaluation.

Results

Wikaytek scrapes validated and reliable COVID-19-related information from reputable sources on Twitter, automatically translates it into Arabic, attaches relevant media (images/video), and generates an audio format using Google text-to-speech. Then, messages are broadcast to WhatsApp. Our evaluation shows that users appreciate receiving "push" information from reliable sources they can trust and prefer the audio format over text.

Conclusions

Wikaytek is a useful and well-received software for diffusing credible information on COVID-19 among Syrian refugees with limited literacy, as it complements the texts with audio messages. The tool can be adapted to diffuse messages about other public health issues among vulnerable communities, extending its scope and reach in humanitarian settings.

Expectations of patient associations from a French Center for Rare Epilepsies

Rare epilepsy centers, also called reference centers in France, have the mission to coordinate care for rare diseases, improve knowledge, and conduct research on rare diseases. Dissemination of knowledge is conducted in collaboration with patient associations. In just a few years, the Internet and social media have become the main source for news and knowledge. We conducted a survey about the use of social media and the expectations of patient associations from a rare epilepsy center. From the 29 associations on our website, 18 (62%) answered the survey, representing about 9000 members. All of the patient associations use social media. Facebook is used by all of them, and most of them also used additional social media channels. 13/18 (72%) associations found that it was easy to get in touch with our center and almost all partner associations were satisfied with the information published on our website (17/18, 94%). Eight patient associations (8/15, 53%) expected more information from us regarding scientific news (10/13) and clinical trials (8/13). Despite the existence of an active website and a monthly newsletter, the family associations interacting with our rare epilepsy center still want to collaborate even more with us. The use of social media by the rare epilepsy centers might help to fill the gap of the knowledge dissemination.

On the relationship between conspiracy theory beliefs, misinformation, and vaccine hesitancy

At the time of writing, nearly one hundred published studies demonstrate that beliefs in COVID-19 conspiracy theories and misinformation are negatively associated with COVID-19 preventive behaviors. These correlational findings are often interpreted as evidence that beliefs in conspiracy theories and misinformation are exogenous factors that shape human behavior, such as forgoing vaccination. This interpretation has motivated researchers to develop methods for "prebunking," "debunking," or otherwise limiting the spread of conspiracy theories and misinformation online. However, the robust literatures on conspiracy theory beliefs, health behaviors, and media effects lead us to question whether beliefs in conspiracy theories and misinformation should be treated as exogenous to vaccine hesitancy and refusal. Employing U.S. survey data (n = 2,065) from July 2021, we show that beliefs in COVID-19 conspiracy theories and misinformation are not only related to COVID-19 vaccine hesitancy and refusal, but also strongly associated with the same psychological, social, and political motivations theorized to drive COVID-19 vaccine hesitancy and refusal. These findings suggest that beliefs in conspiracy theories and misinformation might not always be an exogenous cause, but rather a manifestation of the same factors that lead to vaccine hesitancy and refusal. We conclude by encouraging researchers to carefully consider modeling choices and imploring practitioners to refocus on the worldviews, personality traits, and political orientations that underlie both health-related behaviors and beliefs in conspiracy theories and misinformation.

Cause and effect: On the antecedents and consequences of conspiracy theory beliefs

Since 2008, hundreds of studies have been published about conspiracy theories, many of which were in reaction to the COVID-19 pandemic. These studies are often motivated by concerns about the influence of exposure to conspiracy theories on beliefs, and the impact of conspiracy theory beliefs on behaviors. Numerous studies identify supportive correlations, concluding implicitly or explicitly that exposure causes belief and that beliefs subsequently cause behavior. We argue that while these causal relationships may exist, such conclusions currently lack robust evidence. We present an alternative model of the relationship between exposure, beliefs, and behaviors that accounts for other potentially causal factors and pathways. We encourage further work into the causal effects of exposure to, and beliefs in, conspiracy theories.

Have beliefs in conspiracy theories increased over time?

The public is convinced that beliefs in conspiracy theories are increasing, and many scholars, journalists, and policymakers agree. Given the associations between conspiracy theories and many non-normative tendencies, lawmakers have called for policies to address these increases. However, little evidence has been provided to demonstrate that beliefs in conspiracy theories have, in fact, increased over time. We address this evidentiary gap. Study 1 investigates change in the proportion of Americans believing 46 conspiracy theories; our observations in some instances span half a century. Study 2 examines change in the proportion of individuals across six European countries believing six conspiracy theories. Study 3 traces beliefs about which groups are conspiring against “us,” while Study 4 tracks generalized conspiracy thinking in the U.S. from 2012 to 2021. In no instance do we observe systematic evidence for an increase in conspiracism, however operationalized. We discuss the theoretical and policy implications of our findings.

Pretrained Transformer Language Models Versus Pretrained Word Embeddings for the Detection of Accurate Health Information on Arabic Social Media: Comparative Study

Background

In recent years, social media has become a major channel for health-related information in Saudi Arabia. Prior health informatics studies have suggested that a large proportion of health-related posts on social media are inaccurate. Given the subject matter and the scale of dissemination of such information, it is important to be able to automatically discriminate between accurate and inaccurate health-related posts in Arabic.

Objective

The first aim of this study is to generate a data set of generic health-related tweets in Arabic, labeled as either accurate or inaccurate health information. The second aim is to leverage this data set to train a state-of-the-art deep learning model for detecting the accuracy of health-related tweets in Arabic. In particular, this study aims to train and compare the performance of multiple deep learning models that use pretrained word embeddings and transformer language models.

Methods

We used 900 health-related tweets from a previously published data set extracted between July 15, 2019, and August 31, 2019. Furthermore, we applied a pretrained model to extract an additional 900 health-related tweets from a second data set collected specifically for this study between March 1, 2019, and April 15, 2019. The 1800 tweets were labeled by 2 physicians as accurate, inaccurate, or unsure. The physicians agreed on 43.3% (779/1800) of tweets, which were thus labeled as accurate or inaccurate. A total of 9 variations of the pretrained transformer language models were then trained and validated on 79.9% (623/779 tweets) of the data set and tested on 20% (156/779 tweets) of the data set. For comparison, we also trained a bidirectional long short-term memory model with 7 different pretrained word embeddings as the input layer on the same data set. The models were compared in terms of their accuracy, precision, recall, F₁ score, and macroaverage of the F₁ score.

Results

We constructed a data set of labeled tweets, 38% (296/779) of which were labeled as inaccurate health information, and 62% (483/779) of which were labeled as accurate health information. We suggest that this was highly efficacious as we did not include any tweets in which the physician annotators were unsure or in disagreement. Among the investigated deep learning models, the Transformer-based Model for Arabic Language Understanding version 0.2 (AraBERTv0.2)-large model was the most accurate, with an F₁ score of 87%, followed by AraBERT version 2–large and AraBERTv0.2-base.

Conclusions

Our results indicate that the pretrained language model AraBERTv0.2 is the best model for classifying tweets as carrying either inaccurate or accurate health information. Future studies should consider applying ensemble learning to combine the best models as it may produce better results.

Narrative elaboration makes misinformation and corrective information regarding COVID-19 more believable

OBJECTIVE

People gather information about health topics from online channels oftentimes awash with misinformation. Investigating this problem during the COVID-19 pandemic is important, as the misinformation effect occurs when misleading details are embedded in narratives and questions. This pilot study investigated whether narrative elaboration increases believability in misinformation statements about COVID-19, and willingness to share these statements online.

RESULTS

Results from our online survey (n = 80) demonstrated that narrative elaboration increased believability in both misinformation and accurate statements, with a more pronounced effect on younger adults. Future research may investigate cognitive vulnerabilities imposed by elaborate narratives embedded in online health misinformation with increased attention on developing misinformation resilience among younger adults.

Online misinformation is linked to early COVID-19 vaccination hesitancy and refusal

Widespread uptake of vaccines is necessary to achieve herd immunity. However, uptake rates have varied across U.S. states during the first six months of the COVID-19 vaccination program. Misbeliefs may play an important role in vaccine hesitancy, and there is a need to understand relationships between misinformation, beliefs, behaviors, and health outcomes. Here we investigate the extent to which COVID-19 vaccination rates and vaccine hesitancy are associated with levels of online misinformation about vaccines. We also look for evidence of directionality from online misinformation to vaccine hesitancy. We find a negative relationship between misinformation and vaccination uptake rates. Online misinformation is also correlated with vaccine hesitancy rates taken from survey data. Associations between vaccine outcomes and misinformation remain significant when accounting for political as well as demographic and socioeconomic factors. While vaccine hesitancy is strongly associated with Republican vote share, we observe that the effect of online misinformation on hesitancy is strongest across Democratic rather than Republican counties. Granger causality analysis shows evidence for a directional relationship from online misinformation to vaccine hesitancy. Our results support a need for interventions that address misbeliefs, allowing individuals to make better-informed health decisions.