The Disinformation Dozen: An Exploratory Analysis of Covid-19 Disinformation Proliferation on Twitter

Nogara, Gianluca; Vishnuprasad, Padinjaredath Suresh; Cardoso, Felipe Maciel; Ayoub, Omran; Giordano, Silvia; Luceri, Luca

doi:10.1145/3501247.3531573

Cited by 32 publications

(19 citation statements)

References 4 publications

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“…We note three unreliable sources in this ranking: childrenshealthdefense.org, thegatewaypundit.com, and zerohedge.com. The most popular low-credibility source was the website of the CHD organization, an antivaccine group led by Robert F Kennedy Jr that became very popular during the pandemic as an alternative and natural medicine site [ 46 , 68 ]. This source was banned from Facebook and Instagram for repeatedly violating their guidelines against spreading medical misinformation in August 2022 [ 69 ].…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

One Year of COVID-19 Vaccine Misinformation on Twitter: Longitudinal Study

Pierri¹,

DeVerna²,

Yang³

et al. 2023

J Med Internet Res

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Background Vaccinations play a critical role in mitigating the impact of COVID-19 and other diseases. Past research has linked misinformation to increased hesitancy and lower vaccination rates. Gaps remain in our knowledge about the main drivers of vaccine misinformation on social media and effective ways to intervene. Objective Our longitudinal study had two primary objectives: (1) to investigate the patterns of prevalence and contagion of COVID-19 vaccine misinformation on Twitter in 2021, and (2) to identify the main spreaders of vaccine misinformation. Given our initial results, we further considered the likely drivers of misinformation and its spread, providing insights for potential interventions. Methods We collected almost 300 million English-language tweets related to COVID-19 vaccines using a list of over 80 relevant keywords over a period of 12 months. We then extracted and labeled news articles at the source level based on third-party lists of low-credibility and mainstream news sources, and measured the prevalence of different kinds of information. We also considered suspicious YouTube videos shared on Twitter. We focused our analysis of vaccine misinformation spreaders on verified and automated Twitter accounts. Results Our findings showed a relatively low prevalence of low-credibility information compared to the entirety of mainstream news. However, the most popular low-credibility sources had reshare volumes comparable to those of many mainstream sources, and had larger volumes than those of authoritative sources such as the US Centers for Disease Control and Prevention and the World Health Organization. Throughout the year, we observed an increasing trend in the prevalence of low-credibility news about vaccines. We also observed a considerable amount of suspicious YouTube videos shared on Twitter. Tweets by a small group of approximately 800 “superspreaders” verified by Twitter accounted for approximately 35% of all reshares of misinformation on an average day, with the top superspreader (@RobertKennedyJr) responsible for over 13% of retweets. Finally, low-credibility news and suspicious YouTube videos were more likely to be shared by automated accounts. Conclusions The wide spread of misinformation around COVID-19 vaccines on Twitter during 2021 shows that there was an audience for this type of content. Our findings are also consistent with the hypothesis that superspreaders are driven by financial incentives that allow them to profit from health misinformation. Despite high-profile cases of deplatformed misinformation superspreaders, our results show that in 2021, a few individuals still played an outsized role in the spread of low-credibility vaccine content. As a result, social media moderation efforts would be better served by focusing on reducing the online visibility of repeat spreaders of harmful content, especially during public health crises.

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Section: Resultsmentioning

confidence: 99%

“…Specifically, we analyzed two types of accounts. First, we investigated the presence and characteristics of users who generated the most reshares of misinformation [ 45 , 46 ], with a specific focus on the role of “verified” accounts. Twitter deems these accounts “authentic, notable, and active” (see [ 47 ]).…”

Section: Introductionmentioning

confidence: 99%

One Year of COVID-19 Vaccine Misinformation on Twitter: Longitudinal Study

Pierri¹,

DeVerna²,

Yang³

et al. 2023

J Med Internet Res

View full text Add to dashboard Cite

show abstract

“…The remainder of the superspreaders consist of (in order of descending number of accounts) "organizations," "intellectuals," "new media," "public service," "broadcast news," and "hard news" accounts. Notable among these accounts are: the prominent anti-vaccination organization, Children's Health Defense, whose chairman, Robert F. Kennedy Jr., was named as one of the top superspreaders of COVID-19 vaccine disinformation [6,33]; the self-described "climate science contrarian" Steve Milloy, who has been labeled a "pundit for hire" for the oil and tobacco industries [47,31]; and the popular Fox News television show host, Sean Hannity, who has been repeatedly accused of peddling conspiracy theories and misinformation on his show [11,43,30].…”

Section: Account Classificationmentioning

confidence: 99%

“…In the health domain, analysis of the prevalence of low-credibility content related to the COVID-19 "infodemic" on Facebook and Twitter showed that superspreaders on both of these platforms were popular pages and accounts that had been verified by the platforms [51]. In 2021, the Center for Countering Digital Hate reported that just 12 accounts -the so-called "disinformation dozen"-were responsible for almost two-thirds of anti-vaccine content circulating on social media [6,33]. This is concerning because eroding the public's trust in vaccines can be especially dangerous during a pandemic [24] and evidence suggests that increased exposure to vaccinerelated misinformation may reduce one's willingness to get vaccinated [27,38].…”

Section: Introductionmentioning

confidence: 99%

Identification and characterization of misinformation superspreaders on social media

DeVerna¹,

Aiyappa²,

Pacheco³

et al. 2022

Preprint

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The world's digital information ecosystem continues to struggle with the spread of misinformation. Prior work has suggested that users who consistently disseminate a disproportionate amount of lowcredibility content -so-called superspreaders -are at the center of this problem. We quantitatively confirm this hypothesis and introduce simple metrics to predict the top misinformation superspreaders several months into the future. We then conduct a qualitative review to characterize the most prolific superspreaders and analyze their sharing behaviors. Superspreaders include pundits with large followings, low-credibility media outlets, personal accounts affiliated with those media outlets, and a range of influencers. They are primarily political in nature and use more toxic language than the typical user sharing misinformation. We also find concerning evidence suggesting that Twitter may be overlooking prominent superspreaders. We hope this work will further public understanding of bad actors and promote steps to mitigate their negative impacts on healthy digital discourse.

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“…However, OSNs have been suffering from a lack of these elements, as their growth have been accompanied with an increase in the number of deceptive and fraudulent accounts that intentionally damage the credibility of online discussions [7]. The activity of such accounts is often associated to online harms tied with the honesty and ethics of conversations, such as the proliferation of hate speech, incitement of violence, and dissemination of misleading and controversial content, as recently observed in debates concerning the Covid-19 pandemic [8,9,10,11,12]. Such fraudulent accounts are recognized as major threats to healthy online conversations, whose activity can potentially exacerbate division on societal issues and affect the sovereignty of elections [13,14,15,16,17].…”

Section: Introductionmentioning

confidence: 99%

How "troll" are you? Measuring and detecting troll behavior in online social networks

Ezzeddine¹,

Luceri²,

Ayoub³

et al. 2022

Preprint

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The detection of state-sponsored trolls acting in misinformation operations is an unsolved and critical challenge for the research community, with repercussions that go beyond the online realm. In this paper, we propose a novel approach for the detection of troll accounts, which consists of two steps. The first step aims at classifying trajectories of accounts' online activities as belonging to either a troll account or to an organic user account. In the second step, we exploit the classified trajectories to compute a metric, namely "troll score", which allows us to quantify the extent to which an account behaves like a troll. Experimental results show that our approach identifies accounts' trajectories with an AUC close to 99% and, accordingly, classify trolls and organic users with an AUC of 97%. Finally, we evaluate whether the proposed solution can be generalized to different contexts (e.g., discussions about Covid-19) and generic misbehaving users, showing promising results that will be further expanded in our future endeavors.

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The Disinformation Dozen: An Exploratory Analysis of Covid-19 Disinformation Proliferation on Twitter

Cited by 32 publications

References 4 publications

One Year of COVID-19 Vaccine Misinformation on Twitter: Longitudinal Study

One Year of COVID-19 Vaccine Misinformation on Twitter: Longitudinal Study

Identification and characterization of misinformation superspreaders on social media

How "troll" are you? Measuring and detecting troll behavior in online social networks

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