A cross-platform analysis of the distribution of COVID-19 conspiracy theories

A cross-platform analysis of the distribution and propagation of conspiracy theories surrounding the COVID-19 pandemic

Topics/keywords: conspiracy theories, COVID-19, coronavirus, misinformation, platform dissemination, cross-platform research

Research Report for the Virtual Data Sprint 2020 Radical Subcultures Online Seminar 6th of March 2020

Filippo Fagnoni

12807087

fagnonifilippo@gmail.com

Josephine Oettle

12801194

josieoettle@hotmail.de

Yonathan Tesfai

10468870

yonathan.tesfai@gmail.com

Veronica Fanzio

12772194

fanzioveronica97@gmail.com

Article’s lead Eating bat soup, invisible 5G radiation waves, New World Order or American bioweapons.

Conspiracy theories have existed since the dawn of civilizations, and have only been intensified in the Internet age. However, the proliferation of social media platforms and the integration of fringe subcultures into the mainstream have provided these conspiracies with an even more fertile breeding ground. What happens then, when a worldwide pandemic is introduced? What kinds of theories are disseminated, where do they live, and where do they originate from? While the bat soup conspiracy can be traced back to videos of the practice, others have mingled with pre-existing conspiracies along the way.

Research questions RQ1: Where do conspiracies about the COVID-19 come from?

RQ2: How do they relate to existing “opaque power” conspiracies?

RQ3: Which conspiracy theories surrounding COVID-19 most prevalent on mainstream platforms such as Youtube and Twitter?

Essay summary This essay examines the occurrence and spread of conspiracy theories surrounding the new coronavirus and COVID-19 disease, and maps their engagement over time on different platforms.

To collect the findings, this research made use of Twitter, YouTube and 4chan videos and posts/Tweets to map these alongside the number of infected people in the most infected countries in the world, against a time period between December 1st, 2019 and March 22nd, 2020. 4CAT, TCAT and DMI’s YouTube Data Tools were used to collect the posts, tweets, videos and engagement data. This data was then visualized in four different ways.

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As indicated by the research, most prominent conspiracy theories surrounding the topic appear to be part of larger, pre-existing conspiracy theories, except the “bat soup” conspiracy.

Furthermore, the COVID-19 pandemic can be seen as a way for especially the QAnon and New World Order conspiracies to further gain strength. The network co-occurence graph shows strong connections between Tweets mentioning these conspiracy theories, and these theories similarly boast the highest view-counts on YouTube. Ultimately, no real evidence of DVW dissemination is found. Conspiracies already existed and “fitted” COVID-19 into their imaginaries.

This research can be used to illuminate the way global events can give rise to conspiracy theories, and the way they can strengthen pre-existing, fringe conspiracies. It also reevaluates the idea that conspiracy theories are only products of these fringes, by asserting that they can also originate on more mainstream platforms.

Introduction The coronavirus COVID-19 pandemic has changed the global order of affairs. Having emerged in Wuhan, China in the waning months of 2019, the novel coronavirus has considerably rearranged the mold of international occurences in the span of only a few months. The World Health Organization (WHO) describes this new virus infection, renamed COVID-19, as caused by a newly discovered coronavirus: a family of viruses that can cause a range of illnesses, from the common cold to more severe ones like SARS - which in 2003 caused over 8,000 infections and 800 deaths globally. What started as a primarily local virus in Wuhan, its reach quickly escalated worldwide, with infections spread all over the globe as of March 2020.

With its ubiquity on social platforms and in the news media, however, the cause of the virus has become a considerable debate on the Internet. Early reports from the World Health Organization indicated the virus was caused by exposures in a Wuhan seafood market , and patient zero may have been exposed as early as November 17, 2019 (World Health Organization, 2020). This report did not, however, stop other stories and narratives from circulating online. One conspiracy theory asserts that the consumption of bat soup in the Wuhan provinces led to the first contraction of

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the virus - a claim that, while since debunked, has remained acknowledged online. Similarly, other kinds of conspiracy theories have spread across different platforms, both in the mainstream and on the fringes. These theories at times contradict each other, at other times complement each other - and even combine with other, pre-existing conspiracies on the complex nexus of the Web. This research report seeks to map these different conspiracy theories, how they differ and propagate across platforms, between countries and how their engagement has changed over the last four months.

Implications A study of the conspiracy theories related to the novel coronavirus (COVID-19) appears of particular relevance for a variety of reasons. In the current state of events, COVID-19 has presented the world with numerous challenges: economic, health and sanitary, humanitarian, and political among others. Additionally, conspiracy theories circulating around the subject seem to have exacerbated its impact and the distress associated with it. Conspiracy theories have a harmful impact on society in many different — but interrelated, ways. When left running wild, baseless conspiracy theories may accelerate the spread of misinformation and the danger of cynicism. At critical times such as the ongoing COVID-19 global pandemic, the spread of misinformation can prove menacing to the health and safety of society as a whole, as well as endangering the truth-seeking apparatus of verifiable journalism and fact-checked, dependable information in service of the public good.

Conspiracy theories, distrust, and misinformation Firstly, it has to be underlined that these theories tend to arise especially in historical periods perceived as uncertain and threatening: in critical moments for society, society itself seeks to

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give coherence and sense to a chaotic world (Jolley & Lamberty, 2020). Possibly, due to its unforeseen and sudden nature, COVID-19 certainly qualifies as such.

Secondly, the main targets of conspiracy theories are generally the groups perceived as powerful, such as high-level politicians, elites, drug companies, or in this case, even the World Health Organization. Differing from classic conspiracism that has been present throughout history, a new type of conspiracism that has been prevalent in the last few years is divergent in one major component: it encapsulates conspiracy without the theory (Muirhead & Rosenblum, 2019). Even if often far-fetched and only sometimes accurate, classic conspiracism attempts to make sense of a complex world, giving order and meaning to events that go against official explanations - and thus, in classic conspiracism, the dots are still mostly coherently connected into a “comprehensive narrative of events� (Muirhead & Rosenblum, 2019). Inversely, the new conspiracism, the type that seems to thrive on the lack of theory and evidence, can be extremely dangerous to the foundations of democracy and truth. Moreover, what validates this new breed of conspiracism is not evidence, but repetition.

In the age of new media, forwarding, reposting, liking and retweeting seem to be the new methods of how accusations are validated, and its implications are profound in the delegitimizing of democratic institutions (Muirhead & Rosenblum, 2019, p. 4). As baseless information is increasingly circulated on the Internet and mainstream social media platforms, distrust in governments and their channels of communication within the population may pose a serious threat to the legitimacy and accuracy of vital information. Even more so in instances of an unusual, global viral pandemic. If distrust runs rampant in a global state of emergency, the negative consequences regarding the safety of individuals and the confidence in government institutions could be significant - and detrimental.

The impact of this distrust, when conspiracy theories orbit around health issues such as COVID19, is directed primarily at medical authorities: leading the endorsers of the conspiracies to avoid medical advice and valid treatments such as vaccines and antibiotics.

As Noah Harari (2020) underlines, to face a pandemic it is necessary to advocate for cooperation, compliance, and solidarity between nations and their citizens as well as at an international level.

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Trust is therefore essential to achieve these goals: people need to have confidence in science, public authorities, and the media (Harari, 2020).

Protecting ourselves, as citizens and political actors, from conspiracy theories is imperative in order to make the healthiest and safest choices in a historical moment that, if improperly handled, can endanger us at the long term. This danger could negatively shape not only the healthcare system but also, and deeply, politics, economy, and culture (Harari, 2020).

Platforms As mentioned above, repetition on various online platforms plays an important role in validating new conspiracism that often lacks evidence and thrives on constant reiteration. As the content travels from subcultural communities to more mainstream platforms, YouTube specifically has been scrutinized for the spread of conspiracies and far right ideas (Tokmetzis, 2019). The amount of such content on the platform was overwhelming, and it is even called out for being the “mothership of online hate� by Tokmetzis (2019). Along with conspiracies, the content available on YouTube ranges from antisemitism, racism to antifeminism (Tokmetzis, 2019).

The present research provides an overview of the history of the conversation around COVID-19 conspiracies on different platforms, namely YouTube, Twitter, and 4chan. This makes it relatable to other events that have occurred internally or externally on the platforms themselves. As the graph shown below in the Findings section depicts, one factor that has been accounted for and put in relation to the conspiracies dataset is the number of infected people (Figure 1). A primary observation is that the growth of contagions corresponds also to an increase in the discourse on different conspiracy theories.

This analysis further allows researchers to understand if and how COVID-19 conspiracy theories differ across platforms, and how users who engage in them are also engaged in discussing other conspiracies.

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It can also be noticed how many COVID-19 conspiracies have been incorporated into pre-existing conspiracies, such as New World Order and QAnon: suggesting that COVID-19 is providing a new alternative path for these conspiracies to strengthen their ideas, attract new followers, and extend them into the virus outbreak narrative.

Further insights on the findings will be provided throughout the report: the mutual engagement of conspiracy theories, the leading actors and sources, and the role of certain platforms in generating and propagating the conspiracies will be seen with more clarity.

Contributing to the discussion on COVID-19 related conspiracies and helping to unmask the underlying related misinformation is therefore fundamental to prevent more individuals from embracing them. This research, with facts and optimism, aims to eventually enhance the sensibility toward the real, negative implications and consequences these conspiracies can lead to.

Individuals who actively endorse COVID-19 conspiracies are, all things considered, more likely to distance themselves from medical authorities, adopting potentially harmful and medically unfounded alternative treatments, incrementing the virus spreading and endangering other individuals. For example, if the preliminary conspiracy theory claiming COVID-19 was a hoax were to be believed, it could have significant ramifications in the disregard for a social distancing policy.

Furthermore, some of these theories have already led to unfortunate cases of racism toward East-Asians, in a worrying resemblance of the attacks inflicted against Jews during the Black Death in Europe, as they were seen by predominant conspiracies as culprits (Jolley & Douglas, 2017).

As Jolley and Douglas (2017) state, one way to strengthen anti�conspiracy arguments can be to present them before conspiracy theories are introduced. Exposing and counterarguing misinformation and conspiracy with clear, informed facts appears to be a crucial step toward minimizing the dangers of conspiracy theories. Moreover, it is a vital measure to avoid the additional spread of pre-existing conspiracies and, hopefully, to prevent new ones from arising.

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COVID-19 Conspiracy Theories Explained Before the findings of this research are discussed, the diverse COVID-19 conspiracy theories are briefly explained. The aim of this is to describe the theories, and clarify which may not be as wellknown or recognized.

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Bat Soup: COVID-19 emerged after videos of individuals in China eating bat soup and allegedly becoming infected surfaced on social media. This theory underlines some of the more racist canards regarding Chinese citizens’ dietary habits, hygiene, and customs.

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American Bioweapon: COVID-19 is a bioweapon engineered and deliberately released by the USA in China during the 2019 World Military Games held in October 2019 in Wuhan.

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Chinese Bioweapon: COVID-19 is a bioweapon engineered and deliberately released by China or accidentally released from the Wuhan Institute of Virology. Whether deliberately released by the Chinese government or through an accident, the Wuhan Institute of Virology stands at the center of this theory.

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General Bioweapon: COVID-19 is a bioweapon, but there is no country that officially has backed its release or creation. This theory holds that COVID-19 is a weapon, but no particular nation-state or political actor claims responsibility or objective.

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5G: COVID-19 is caused by the rollout of 5G technology. As a novel form of wireless communication, 5G’s radio waves cause COVID-19. This theory differs in two strains: individuals who think it is a mind control apparatus, and others who believe it’s simply a health hazard.

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Bill Gates/Event 201: Event 201 was a high-level pandemic exercise hosted in October 2019 by the Bill Gates Foundation and the Johns Hopkins Center for Health and Security.

It simulated an outbreak of a novel coronavirus transmitted from bats over pigs and then to people (Johns Hopkins Center for Health Security, World Economic Forum & Bill and Melinda Gates Foundation, 2019). The conspiracy contains the claim that the event was organized by Bill Gates as a preparation for the current COVID-19 outbreak and possibly that Bill Gates released the virus.

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NWO (New World Order): COVID-19 was released by a secretive power elite seeking to create global chaos with the ultimate aim of establishing a clandestine totalitarian world government which will replace all sovereign nation-states.

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QAnon: QAnon followers believe that the United States is run and orchestrated by a ring of powerful liberal elites that make up the “deep state”. Trump is the main figure fighting the corruption of the deep state, and this theory holds that the deep state generated COVID-19 to damage Trump’s reputation before the 2020 election cycle and his reelection

prospects.

Trump is the main figure fighting the deep state’s corruption and it is believed that the deep state generated the COVID-19 pandemic to damage Trump’s reputation before the 2020 election cycle and ultimately his re-election prospects -

Big Pharma/Anti Vax: Followers of the Big Pharma conspiracy theory believe pharmaceutical companies, politicians, and others are secretly working together against the public interest (Blaskiewicz, 2013, p. 259). In the case of COVID-19, anti-vaccine groups posted links to a patent for coronavirus in 2015, thus spreading the idea that the government had launched the virus, apparently to make money off a possible vaccine (Dickson, 2020). Anti-Vax groups are also afraid the government could use the virus to impose obligatory vaccinations on them.

Findings One of the key findings shows that American Bioweapon, New World Order, Bill Gates (Event 201), and Bat Soup theories are the most prominent conspiracies. Furthermore, all of the analysed platforms pick up on the COVID-19 conspiracy theories in January - almost two months after the supposed patient zero in Hubei province. Most importantly, the prominent conspiracy theories surrounding this topic tend to be part of larger conspirative narratives. Namely, the Bat Soup conspiracy may be the only one that is discriminatory in nature against Chinese people per se, and may be propagated on a racist basis. The investigation into YouTube views hints that COVID-19 paved the way for some already existing conspiracies, particularly QAnon and New 9

World Order, to strengthen their ideas with the COVID outbreak as a guise to bolster their movements. While examining the network of co-occurrence links between tweets, an affinity between the New World Order and QAnon clusters emerges, as they probably share similar concerns regarding “shadow governments�. In the view of these conspiracists and their followers, real political power does not belong to publicly elected representatives but rather to unknown, private actors who make decisions behind the scenes. In particular, New World Order believers are convinced that a few powerful elites would form an authoritarian world government that would rule all nations, in a situation where nation-states would no longer exist.

The New World Order is connected almost entirely to the Bioweapon conspiracy, which seems fairly rational - for a new world order to take over, the world must be propelled into utter chaos: a bioweapon is certainly a way to achieve this.

Finding 1: This research found no real evidence of a specific Deep Vernacular Web dissemination of COVID-19 conspiracies. What is meant by Deep Vernacular Web, or DVW, is the fringe platforms and discussions for such as 4chan that are part of a broader, subcultural environment (Tuters et al., 2018). In past research, the DVW comprised an abundance of conspiracy theory dissemination. The conspiracy theories circulated in the timeframe are quite balanced between both 4chan and mainstream social media platforms, and do not hint that fringe platforms such as 4chan were the sole architects or propagators of COVID-19 conspiracies.

Examining the Beeswarm graph (Figure 1), it can be noticed that nearly all the platforms - Twitter, Youtube and 4chan - pick up on the different conspiracies by mid-January latest. Additionally, the posts about COVID-19 conspiracy theories are relatively balanced between the different platforms. Around the same time in mid-January, the news media started to report on the conspiracies - except for American Bioweapon, which they picked up on far later, around the middle of March. The 5G conspiracy seemed to build engagement on Twitter, particularly when the virus spread more across Europe and consequently the USA (Figure 1).

Another intriguing finding is that all conspiracy posts originated on Youtube, with the exception of the Bill Gates/Event 201 conspiracy deriving from Twitter and the American Bioweapon originating from 4chan. This deviates from past research on conspiracy theories like Pizzagate

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and QAnon (Tuters et al., 2018) that firmly originate from 4chan and other fringe, subcultural environments as opposed to more mainstream platforms.

The New World Order beeswarm in Figure 1 stands out, as a Twitter spike is visible at the beginning of March. An explanation therefore could be the CPAC attendee who tested positive for the coronavirus on March 7th, the same time as the spike. Another event corresponding with this peak could be President Trump’s visit to the CDC on the same day.

A most potentially significant finding through the beeswarm graph and data collected for its creation is that, unlike previous research into the origin point of conspiracies such as Pizzagate (Tuters et al. 2018), many of the COVID-19 conspiracies inspected in this research report originated from parts of the web other than 4chan. The assumption that 4chan might be the culprit in the origin of COVID-19 related conspiracy theories stems from previous research into the role that 4chan has had in the formation and dissemination of conspiracy theories into mainstream media. According to the “Pizzagate” conspiracy research conducted by Tuters et al., researchers found that over the course of 25 hours starting on 3 November 2016, anons on the /pol/ board of 4chan dug deeply into an accumulation of John Podesta’s private emails that were obtained by Russian hackers and leaked by Wikileaks’ Julian Assange. John Podesta was Hillary Clinton’s campaign manager during her presidential campaign of 2016, and it is widely believed that the scandal - Russian hacking of the email server - so close to Election Day may have ultimately cost her the election. Within the short time period of 25 hours, anonymous contributors to /pol/ formed a narrative later amplified by a novel right-wing media network in which repetition, variation, and circulation of false claims and baseless portrayals of events are intensifying the shift to a “post-truth”1 world (Tuters et al., 2018). Similarly, in the DMI Winter School 2020 conducted at the University of Amsterdam, the Conspiracy Creation Techniques project was able to trace the origin of the “Epstein didn’t kill himself” conspiracy theory to 4chan, following the death of disgraced financier Jeffrey Epstein in his jail cell (De Zeeuw et al., 2020).

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Post-truth, in media studies and in related fields, relates to the circumstances in which objective or verified facts are increasingly less influential in shaping public opinion in contrast to personal beliefs or basing information on alternative facts. Authors such as Benkler have suggested that a growing number of fake news purveyors and a hyper-polarized media ecosystem are the prime suspects in this state of information disorder.

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This particular research found that the news of Epstein’s death was reported on 4chan /pol/ a full hour before the news broke on American mainstream news media, and further highlighted the rapid propagation of a 4chan-based conspiracy theory into a memetic phrase extensively used on social media in the following weeks. “Epstein didn’t kill himself” became a pervasive meme online as rumours and speculation on Epstein’s cause of death took social media by storm, before becoming just another Internet joke. In this context, the research on COVID-19 conspiracies initially hypothesized that there would be a great chance of conspiracies relating to the topic would originate on 4chan - but as Figure 1 illustrates, this was not entirely the case.

To conclude the findings and discussion regarding the beeswarm graph (Figure 1), an inquiry that this section attempts to answer is: while previous research on origins of conspiracy theories on 4chan confirmed their inception on fringe platforms, where did COVID-19 conspiracies then originate? Why did they originate elsewhere? Although this report cannot present concrete answers to these questions, discussions on the findings sparked a few plausible explanations for this outcome.

Firstly, COVID-19 is presently a dominant and relevant global topic, and the pandemic has affected many regions and countries around the world along with their economies and health care systems. Because of this global impact and due to the gravity of the subject, COVID-19 is not comparable as a topic of interest to more niche topics such as the US presidential election candidates in 2016 (Pizzagate), the New World Order topic of discussion, or QAnon (deep state entrenched in American politics). Many conspiracy theories that are discussed on 4chan and similar fringe platforms are typically adherent of niche environments - and although conspiracism seems to be breaking through mainstream discussion as of late, niche environments such as 4chan were destinations for “politically incorrect” topics. Namely, the /pol/ board on 4chan is short for “Politically Incorrect”. Since COVID-19’s relevance is characterized by its global reach, its potential worldwide economic consequences, and a general sense of disarray, outlets (as well as users) on mainstream platforms may have begun reporting and discussing on COVID-19 in speculative manners outside the niche fringe portions of the Web.

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Secondly, the confusion and disruption caused by the unfamiliarity of COVID-19 as an illness may be a reason for conspiracy theories to originate from a variety of online platforms. Being a novel strain of a virus, the initial mystery surrounding the virus may have prompted conspiratorial discussion. At the beginning, and somewhat even in the present, not even health care professionals and virology experts had all the answers concerning the virus. There was plenty of debate on the proper causes, measures, precautions, and remedies of the virus. Virology experts refrained from making initial assumptions and the fact that no one had concrete answers about COVID-19 may have led individuals to express their own beliefs, without substantiated information, and share it online. From this overload of non-verifiable information, there is a high possibility that conspiracy theories were born out of doubts and uncertainties and propagated on digital platforms.

Lastly, diverse political motivations may be a plausible explanation for the conspiracies’ origins on platforms other than 4chan. Governmental bodies and political actors have many interests in limiting damaging information on COVID-19 for various reasons - among them, the management of their stance in the global (and mainly financial) order of affairs. Due to these interests, individuals who believe their governments and mainstream media are not communicating the complete truth about COVID-19’s impact may be driven to look for information on other platforms, such as YouTube and Twitter. A few examples of this could be China’s or Russia’s alleged underreporting of COVID-19 cases and deaths (Reevel, 2020), along with the Chinese government’s efforts to silence some health care professionals on the initial outbreak of the virus (Buckley, 2020). The lack of trust in government communication, however, may prove to be a much bigger conversation in future research on similar topics - and may pose a problem in the dissemination of “alternative” facts or beliefs online.

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Figure 1: Beeswarm graph representing the number of tweets, YouTube videos, 4chan posts and media articles along with the number of COVID-19 infected people in the most infected countries in the world. The time frame is December 1st, 2019 until March 24th, 2020. High resolution image: https://imgur.com/a/Tvk8sxS

Finding 2: The most prominent conspiracy theories surrounding COVID-19 tend to be part of larger, already existing conspirative narratives.

Through closed reading and a comparative analysis of a large spreadsheet containing 4chan, Twitter and YouTube data on the conspiracy theories, further implicates that the Chinese Bioweapon, New World Order, QAnon, and General Bioweapon conspiracies are the most prominent conspiracies discussed. This observation can be also drawn of their respective YouTube views (Figure 2) and engagement (Figure 3). As explained later, engagement here includes likes, dislikes, and comments on the YouTube videos in question.

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While analysing the Youtube views for the most prominent COVID-19 related conspiracies (Figure 2), the ties of these conspiracies to already existing ones are revealed. The high view count for the QAnon and New World Order (NWO) conspiracy theories right from the beginning of December makes this relationship quite clear. While other conspiracy theories on the graph begin to emerge in late January, the QAnon and NWO are already prevalent beforehand. At the same time, the high view count could hint that COVID-19 paved the way for these conspiracies to strengthen or further their ideologies with the COVID-19 outbreak. The Big Pharma conspiracy seems to have risen in relative Youtube views later than others, in March, and continues to grow. The reason for this may have to do with the health insurance issues in the USA as well as the debate on Medicare for All, a pivotal issue in the US Presidential Primaries and upcoming general election.

Beyond the timeframe of this research, the growth of this theory may fluctuate in either direction. The Bat Soup conspiracy, with a lot of views and prevalence from late January until mid-February, dies off in interest and views on Youtube and remains flat in the time after a smaller peak in mid-February.

Figure 2: Graph representing COVID-19 related conspiracies on Youtube and their relative views.

The time frame is December 1st, 2019 until March 24th, 2020. High resolution image: https://imgur.com/a/mZ0Yv2M. Source: Gabriele Colombo 15

The engagement around the prominent conspiracy theories surrounding COVID-19 show to be similar to the views of those conspiracies on YouTube, albeit with some differences (Figure 3).

The similarities between the views and engagement graphs are to be expected, because on YouTube there is a tendency for engagement (likes, dislikes, comments) to somewhat mirror the amount of views.

A finding that surfaced was that both the views and engagement around the American Bioweapon conspiracy theory started picking up only in the initial days of February. Compared to other conspiracy theories on Figure 3, the American Bioweapon theory emerges and begins to exhibit peaks later than a majority of the other conspiracies. After closer inspection of daily infections in China, it seems that this theory began to be engaged with as China was launched into its exponential growth phase (Worldometer, n.d.). As the beginning of February only witnessed cases in China and COVID-19 was nowhere near a global emergency as it is currently, a rapid increase in Chinese infection cases may have instigated discussions and theorizations regarding a possible American-made bioweapon.

In conclusion to the YouTube data findings, it must be noted that engagements, over views, might be a more valuable insight into this kind of research. Due to the importance of YouTube comments in the formation of discussions and opinions, this metric may prove more fruitful in comprehending the beliefs of users or, in this case, possible conspiracy theory believers.

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Figure 3: Graph representing COVID-19 related conspiracies on Youtube and their relative engagement. The engagement includes likes, dislikes, and comments on the videos. The time frame is December 1st, 2019 until March 24th, 2020. High resolution image: https://imgur.com/a/vaZOwL3. Source: Gabriele Colombo Finding 3: Co-occurrence link clusters heavily reinforce the previous finding that the most prominent conspiracy theories surrounding COVID-19 are interconnected to pre-existing conspiracy theories such as New World Order and QAnon.

These are the colours for each platform on the network graph in Figure 4: 4chan = green, red = youtube, blue = twitter and any other colour = spike.

The foremost observation when examining the network co-occurrence links between tweets is that an affinity exists between the New World Order and QAnon conspiracy clusters. A possible explanation for their affinity can be their shared and similar concerns regarding the “shadow governments�. Both of these conspiracy theories believe in an existing global elite plotting to run the world by replacing sovereign nation-states and establishing one world government. These conspiracies tend to be more interconnected with the COVID-19 pandemic possible due to the fact that believers of QAnon and New World Order see COVID-19 as a catalyst of global chaos: with worldwide disorder, the ground is thus more fertile for an obscure takeover by a new, 17

powerful world government (NWO) or removal of the “Deep State” (QAnon). Moreover, the edges around QAnon are quite evenly distributed between the Hoax and Bioweapon conspiracy.

After Trump recognised the pandemic as a real threat following a rather bizarre, undermining attitude in the initial days of the worsening outbreak, QAnon participants presumably needed to formulate a narrative on the origins and topic of the virus. This could stem from the fact that most QAnon followers believe President Trump is an important figure in the fight against the “deep state”. At first, QAnon followers could have propagated the idea that the virus was not as harmful as health experts stated, but when President Trump changed his narrative, they modified theirs to stay in line with one of the most important figures of their movement.

In contrast, the New World Order cluster is almost entirely connected to the Bioweapon cluster, instead of connecting to any other COVID-19 related conspiracy. The Bioweapon conspiracy may fit best into the NWO beliefs. For the believers of this theory, by spreading a novel, uncertain, and possibly fatal virus across the world, the global elite would capitalize on current politicians, institutions and political structures struggling under chaos and distrust.

Moreover, a reason why the 5G conspiracy theory appears prominently on the beeswarm graph (Figure 1) but not in the co-occurrence graph (figure 4) is that the link co-occurrence is between hashtags and keywords. Our queries did not specifically target hashtags per se, but keywords instead. Since this research had a set of specific queries for each conspiracy theory (not specific hashtags), the nature of Twitter’s hashtags function may have created discrepancies between keywords, queries, and hashtags. Because of this, tweets containing the ‘5G’ keyword may have not included a hashtag. In this instance on Figure four, each node is a tweet, and each edge is a link.

Finally, we would like to argue that this network (Figure 4) highlights how even relatively novel accounts for how this coronavirus emerged, are nonetheless incorporated into existent conspiracy theories.

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Figure 4: Network graph of co-occurrence links between tweets that reference particular conspiracy theories. The time frame is December 1st, 2019 until March 24th, 2020. High resolution image: https://imgur.com/a/Qp9rtCs

Methods This research report aims to map where conspiracies about the COVID-19 come from and how they relate to existing “opaque power� conspiracies. We also try to find out which conspiracy theories surrounding COVID-19 are most prevalent on mainstream platforms such as Youtube and Twitter.

We expect most conspiracies to originate from 4chan and other fringe websites. However, this hypothesis could not be confirmed. In fact, the conspiracies were relatively balanced between platforms.

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As a first step to answer the research questions, an expert list of COVID-19 related conspiracy theories was conducted by a conspiracy expert and by additionally close reading news articles and watching posts and videos concerning the theme. The most prominent conspiracy theories identified are the following: QAnon, American Bioweapon (non-country specific), Chinese Bioweapon, American Bioweapon, New World Order, Bill Gates/Event 201, Bat Soup, Hoax, Big Pharma/Anti Vaxx and 5G. Consecutively, we queried the chosen conspiracies relating to COVID-19 on three platforms consecutively: 4chan, Twitter and Youtube, thereby using the tools 4CAT, TCAT and the Youtube Data Tools application. To properly allow the analysis of the COVID-19 posts, datasets were set up on the different tools. After discussions in the research groups, lists of queries were formulated to further analyse the size and influence of the diverse conspiracy theories. As part of the Digital Methods Initiative (DMI) at the University of Amsterdam, DMI is one of Europe’s leading Internet research groups. Consisting of new media researchers, professors, and PhD candidates, the DMI designs tools and methods for the repurposing of online devices and platforms for digital research into social and political issues. Because of this initiative and due to the nature of academic research aims in the field, the tools and methods used in this report are appropriate to address our research objectives.

The first platform analyzed was 4chan, and the aim was to obtain the frequency of posts that mention the individual conspiracies overtime. The methodology used in this report therefore makes use of 4CAT, a digital tool developed by OILab at the University of Amsterdam (Version 1.0; Peeters & Hagen, 2018), in order to analyze when and if 4chan users talked about COVID-19 conspiracies. Thus, a dataset with COVID-19 posts on 4chan was created by running a query with the parameters ["/cvg/"|"coronavirus general"] on the board /pol/ between 01-12-2019 and 2403-2020. This timeframe was selected to gain a full overview of the outbreak since the first case in China was mentioned publically.

In a subsequent step, the individual conspiracy theories around COVID-19 were queried in the above-mentioned dataset on 4CAT. The goal was to obtain the frequency of posts mentioning the individual conspiracies, per day. Each conspiracy was queried separately. Figure five

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illustrates the parameters used for each query. Hence, the frequencies were downloaded and then added manually to the spreadsheet in separate sheets for each conspiracy.

Figure 5: Parameters for the conducted 4cat queries on the /cvg/ dataset for the individual COVID-19 conspiracy theories After querying 4chan, the same procedure was used for Twitter with the Tool DMI-TCAT, a tool developed by the Digital Methods Initiative (Borra & Rieder, 2014). The tool aided us in obtaining the frequency of tweets that mention each conspiracy over time, as well as the engagement on the tweets. To query the various conspiracies on TCAT, we used a dataset consisting of the 30,767,646 tweets mentioning Coronavirus by inserting [corona* OR COVID*] in the parameter “query�. The time frame for the Twitter dataset was between 28-01-2019 and 24-03-2020.

Subsequently, every COVID-19 related conspiracy was queried within that dataset separately and the tweet statistics downloaded. The reason for a shorter timeframe in the Twitter dataset (January 28th, 2019 vs. December 1st, 2019 for 4chan) was that the Twitter dataset supplied for this research was not as exhaustive as the 4chan dataset offered by 4CAT.

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The following parameters were inserted in “query” for: 1. QAnon: “qanon” OR “cabal” OR “trust the plan” OR “the storm” OR “great awakening” OR “wwg1ga” OR “wwg1waworldwide” OR “thestormishere” 2. Chinese bioweapon: “china” AND “bioweapon” 3. American bioweapon: “bioweapon” AND “americ*; bioweapon” AND “military world games”; military world games 4. 5G: “5G” 5. Bill Gates / Event 201: “event 201” 6. NWO: “nwo” OR “new world order” OR “depopulation” OR “population control” 7. Bat soup: “bat soup” 8. Hoax: “hoax” 9. Big Pharma: “big pharma” OR “anti vax” The methodology furthermore made use of the Youtube Data Tools2 (YTDT) “Video List Module” (Version 1.10; Rieder, 2015), to gain the number of views, likes, dislikes and comments per day from Youtube videos for each conspiracy around COVID-19. The numbers were then added to a large, shared Google spreadsheet containing separate sheets for each individual theory chosen.

Each conspiracy theory had several queries with different parameters always containing coronavirus/COVID and the name of the conspiracy and/or another word connected to the theory (e.g.: coronavirus bioweapon america). The query is supposed to be similar to how a “normal” person interested in a conspiracy would search for it on youtube. The following shows the Parameters entered in “Search Query” for each query on the different conspiracies: 1. QAnon: [cornavirus qanon]; [coronavirus cabal]; [coronavirus trust the plan]; [coronavirus the storm]; [coronavirus great awakening]; [coronavirus wwg1ga]; [coronavirus wwg1waworldwide]; [coronavirus thestormishere] 2. Chinese Bioweapon: [coronavirus china weapon]; [coronavirus wuhan virology]; [coronavirus china lab]

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The Youtube Data Tools is a tool created by Bernhard Rieder at the University of Amsterdam for the Digital Methods Initiative.

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3. American Bioweapon: [coronavirus bioweapon america]; [coronavirus Military World Games]; [COVID bioweapon america]; [COVID Military World Games] 4. 5G: [coronavirus radiation]; [coronavirus sickness]; [coronavirus poisoning] 5. Bill Gates: [coronavirus Bill Gates]; [coronavirus Event 201]; [coronavirus Gates Foundation] 6. NWO: [coronavirus new world order depopulation]; [coronavirus new world order population control]; [coronavirus NWO] 7. Bat Soup: [coronavirus bat soup]; [COVID bat soup] 8. Hoax: [coronavirus hoax] 9. Big Pharma: [coronavirus big pharma]; [coronavirus antivax]

The timeframe for all queries was between 01-12-2019 and 24-03-2020, while the search was made for each day. The data was extracted for each day of the given time and ranked by date, while the parameter iterations set on 10. The number of views per day on Youtube for each conspiracy theory were counted manually in Excel. To avoid iterations, double URLs were removed manually in Excel for each theory, before counting the number of views. The retrieved Youtube data was thereapon added to the spreadsheet.

All of the platforms’ data were incorporated in a large Google spreadsheet in different sheets for each conspiracy theory, utilized for better analysis, comparison and visualization of the data. For our visualizations of the tweets, we imported the URLS of the co-occurrence links to Gephi, an open-source visualization and exploration software (https://gephi.org/). This research furthermore made use of Raw Graphs (https://rawgraphs.io/) to create Figure two, three and four.

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Financial Times. Retrieved from https://www.ft.com Jolley, D., & Douglas, K. M. (2017). Prevention is better than cure: Addressing anti‐vaccine conspiracy theories. Journal of Applied Social Psychology, 47(8), 459-469.

Jolley, D., & Lamberty, P. (2020, February 28). Coronavirus is a breeding ground for conspiracy theories – here’s why that’s a serious problem. The Conversation. Retrieved from https://theconversation.com Johns Hopkins Center for Health Security, World Economic Forum, & Bill and Melinda Gates Foundation. (2019, October 18). The Event 201 scenario. Retrieved from http://www.centerforhealthsecurity.org/event201/scenario.html 24

Ma, A. (2018, August 19). Barging into your home, threatening your family, or making you disappear: Here's what China does to people who speak out against them. Business Insider. Retrieved from https://www.businessinsider.com Peeters, S., & Hagen, S. (2018). 4CAT: Capture and Analysis Toolkit (Version 1.0) [Computer Software]. Retrieved from https://4cat.oilab.nl/ Reevell, P. (2020, March 21). Why is Russia reporting so few COVID-19 cases? Some say it's a cover-up. ABC News. Retrieved from https://abcnews.go.com Rieder, Bernhard (2015). YouTube Data Tools (Version 1.10) [Computer Software]. Retrieved from https://tools.digitalmethods.net/netvizz/youtube/ Tokmetzis, D. (2019, October 28). How They Did It: Exposing Right-Wing Radicalization on YouTube. Retrieved from https://gijn.org/2019/10/28/how-they-did-it-exposing-rightwing-radicalization-on-youtube/ Tuters, M., JokubauskaitÄ—, E., & Bach, D. (2018). Post-Truth Protest: How 4chan Cooked Up the Pizzagate Bullshit. M/C Journal, 21(3).

World Health Organization. (2020). Novel Coronavirus (2019-nCoV). Situation Report 1 (Report No.1). Retrieved from https://www.who.int/docs/defaultsource/coronaviruse/situation-reports/20200121-sitrep-1-2019ncov.pdf?sfvrsn=20a99c10_4 Worldometer. (n.d.). Coronavirus Cases. Retrieved March 6, 2020, from https://www.worldometers.info/coronavirus/coronavirus-cases/

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Funding This research was conducted during the Virtual Data Sprint 2020: Radical Subcultures Online. This data sprint was facilitated by New Media professors at the University of Amsterdam.

Competing interests No potential conflict of interest between the authors of this research occurred.

Ethics This research required no human nor animal experiments. The research method was approved by researchers at the University of Amsterdam.

Copyright This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided that the original author and source are properly credited.

Please consult our data sharing policy before submission.

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