Following the 2016 U.S. presidential election, many have expressed concern about the effects of false stories (“fake news”), circulated largely through social media. We discuss the economics of fake news and present new data on its consumption prior to the election. Drawing on web browsing data, archives of fact-checking websites, and results from a new online survey, we find: (i) social media was an important but not dominant source of election news, with 14 percent of Americans calling social media their “most important” source; (ii) of the known false news stories that appeared in the three months before the election, those favoring Trump were shared a total of 30 million times on Facebook, while those favoring Clinton were shared 8 million times; (iii) the average American adult saw on the order of one or perhaps several fake news stories in the months around the election, with just over half of those who recalled seeing them believing them; and (iv) people are much more likely to believe stories that favor their preferred candidate, especially if they have ideologically segregated social media networks.

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Social Media and Fake News in the 2016 Election

With the onset of the COVID-19 pandemic, social media has rapidly become a crucial communication tool for information generation, dissemination, and consumption. In this scoping review, we selected and examined peer-reviewed empirical studies relating to COVID-19 and social media during the first outbreak from November, 2019, to November, 2020. From an analysis of 81 studies, we identified five overarching public health themes concerning the role of online social media platforms and COVID-19. These themes focused on: surveying public attitudes, identifying infodemics, assessing mental health, detecting or predicting COVID-19 cases, analysing government responses to the pandemic, and evaluating quality of health information in prevention education videos. Furthermore, our Review emphasises the paucity of studies on the application of machine learning on data from COVID-19-related social media and a scarcity of studies documenting real-time surveillance that was developed with data from social media on COVID-19. For COVID-19, social media can have a crucial role in disseminating health information and tackling infodemics and misinformation.

What social media told us in the time of COVID-19: a scoping review.

With the onset of COVID-19 pandemic, social media has rapidly become a crucial communication tool for information generation, dissemination, and consumption. In this scoping review, we selected and examined peer-reviewed empirical studies relating to COVID-19 and social media during the first outbreak starting in November 2019 until May 2020. From an analysis of 81 studies, we identified five overarching public health themes concerning the role of online social platforms and COVID-19. These themes focused on: (i) surveying public attitudes, (ii) identifying infodemics, (iii) assessing mental health, (iv) detecting or predicting COVID-19 cases, (v) analyzing government responses to the pandemic, and (vi) evaluating quality of health information in prevention education videos. Furthermore, our review highlights the paucity of studies on the application of machine learning on social media data related to COVID-19 and a lack of studies documenting real-time surveillance developed with social media data on COVID-19. For COVID-19, social media can play a crucial role in disseminating health information as well as tackling infodemics and misinformation.

What social media told about us in the time of COVID-19: a scoping review

Background: COVID-19 is one of the greatest threats to human beings in terms of health care, economy, and society in recent history. Up to this moment, there have been no signs of remission, and there is no proven effective cure. Vaccination is the primary biomedical preventive measure against the novel coronavirus. However, public bias or sentiments, as reflected on social media, may have a significant impact on the progression toward achieving herd immunity.
Objective: This study aimed to use machine learning methods to extract topics and sentiments relating to COVID-19 vaccination on Twitter.
Methods: We collected 31,100 English tweets containing COVID-19 vaccine–related keywords between January and October 2020 from Australian Twitter users. Specifically, we analyzed tweets by visualizing high-frequency word clouds and correlations between word tokens. We built a latent Dirichlet allocation (LDA) topic model to identify commonly discussed topics in a large sample of tweets. We also performed sentiment analysis to understand the overall sentiments and emotions related to COVID-19 vaccination in Australia.
Results: Our analysis identified 3 LDA topics: (1) attitudes toward COVID-19 and its vaccination, (2) advocating infection control measures against COVID-19, and (3) misconceptions and complaints about COVID-19 control. Nearly two-thirds of the sentiments of all tweets expressed a positive public opinion about the COVID-19 vaccine; around one-third were negative. Among the 8 basic emotions, trust and anticipation were the two prominent positive emotions observed in the tweets, while fear was the top negative emotion.
Conclusions: Our findings indicate that some Twitter users in Australia supported infection control measures against COVID-19 and refuted misinformation. However, those who underestimated the risks and severity of COVID-19 may have rationalized their position on COVID-19 vaccination with conspiracy theories. We also noticed that the level of positive sentiment among the public may not be sufficient to increase vaccination coverage to a level high enough to achieve vaccination-induced herd immunity. Governments should explore public opinion and sentiments toward COVID-19 and COVID-19 vaccination, and implement an effective vaccination promotion scheme in addition to supporting the development and clinical administration of COVID-19 vaccines.

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Tweet Topics and Sentiments Relating to COVID-19 Vaccination Among Australian Twitter Users: Machine Learning Analysis.

The COVID-19 'infodemic' continues to undermine trust in vaccination efforts aiming to bring an end to the pandemic. However, the challenge of vaccine hesitancy is not only a problem of the information ecosystem and it often has little to do with the vaccines themselves. In this Perspective, we argue that the epidemiological and social crises brought about by COVID-19 have magnified widely held social anxieties and trust issues that, in the unique circumstances of this global pandemic, have exacerbated skepticism toward vaccines. We argue that trust is key to overcoming vaccine hesitancy, especially in a context of widespread social uncertainty brought about by the pandemic, where public sentiment can be volatile. Finally, we draw out some implications of our argument for strategies to build vaccine confidence. 

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An epidemic of uncertainty: rumors, conspiracy theories and vaccine hesitancy

Focussing in detail on one key component of the infodemic surrounding COVID-19, this article traces the dissemination dynamics of rumours that the pandemic outbreak was somehow related to the rollout of 5G mobile telephony technology in Wuhan and around the world. Drawing on a mixture of quantitative and qualitative methods including time-series analysis, network analysis and in-depth close reading, our analysis shows the dissemination of the rumour on Facebook from its obscure origins in pre-existing conspiracist groups through greater uptake in more diverse communities to substantial amplification by celebrities, sports stars and media outlets. The in-depth tracing of COVID-related mis- and disinformation across social networks offers important new insights into the dynamics of online information dissemination and points to opportunities to slow and stop the spread of false information, or at least to combat it more directly with accurate counterinformation.

https://journals.sagepub.com/doi/pdf/10.1177/1329878X20946113

‘Corona? 5G? or both?’: the dynamics of COVID-19/5G conspiracy theories on Facebook

There is a growing concern around the dependency of news organisations on platforms like Facebook for audience traffic. However, scholars are still working out the extent of this dependency and how...

Facebook, news media and platform dependency: The institutional impacts of news distribution on social platforms:

This article describes the emerging genre of ‘social news’ – characterised by a ‘born-digital’ form of journalism which is both symptomatic of and a pragmatic response to the logics of social media...

What’s newsworthy about ‘social news’? Characteristics and potential of an emerging genre:

Social media platforms and news organisations alike are struggling with identifying and combating visual mis/disinformation presented to their audiences. Such processes are complicated due to the enormous number of media items being produced, how quickly media items spread, and the often-subtle or sometimes invisible-to-the-naked-eye nature of deceptive edits. Despite knowing little about the provenance and veracity of the visual content they encounter, journalists have to quickly determine whether to re-publish or amplify this content, with few tools and little time available to assist them in such an evaluation. With the goal of equipping journalists with the mechanisms, skills, and knowledge to be effective gatekeepers and stewards of the public trust, this study reviews current journalistic image verification practices, examines a number of existing and emerging image verification technologies that could be deployed or adapted to aid in this endeavour, and identifies the strengths and limitations of the most promising extant technical approaches. While oriented towards practical and achievable steps in combating visual mis/disinformation, the study also contributes to discussions on fact-checking, source-checking, verification, debunking and journalism training and education.

Visual Mis/disinformation in Journalism and Public Communications: Current Verification Practices, Challenges, and Future Opportunities

This article brings together perspectives from digital media studies and journalism scholarship to propose a working definition of digital journalism that can guide scholarship and applied research in this field. We define digital journalism as “those practices of newsgathering, reporting, textual production and ancillary communication that reflect, respond to, and shape the social, cultural and economic logics of the constantly changing digital media environment.” We elaborate and illustrate this definition through a discussion of the co-evolving relationship of journalism with the Internet and social media platforms since the 2000s and outline in detail how social news outlets such as BuzzFeed are paradigmatic examples of these dynamics and relationships. The article concludes by emphasizing the urgent need for both the study and practice of digital journalism in the public interest, especially in the context of an increasingly platformed and closed media system. We focus particularly on the methodological challenges and threat to public oversight that recent moves to platform enclosure and lockdown represent and provide some suggestions as to how these might be addressed.

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Edward Hurcombe

Papers

‘Corona? 5G? or both?’: the dynamics of COVID-19/5G conspiracy theories on Facebook

Facebook, news media and platform dependency: The institutional impacts of news distribution on social platforms:

What’s newsworthy about ‘social news’? Characteristics and potential of an emerging genre:

Visual Mis/disinformation in Journalism and Public Communications: Current Verification Practices, Challenges, and Future Opportunities

Digital Journalism as Symptom, Response, and Agent of Change in the Platformed Media Environment