While conspiracy theories have long been understood as irrational narratives produced by extremists in the margins of political and social life, a body of humanities scholarship considers them as critical responses to the complexities and uncertainties of (post)modern life (Knight 2000). While conspiracy theory is often imagined to be a right-wing preoccupation, with the pandemic we have seen the emergence of new "diagonal movements" that cut across traditional left/right distinctions sharing the conviction that all power is conspiracy (Slobodian & Callison 2021).In this summer school project, we set out to make an empirical contribution to the study of online conspiracism by examining conspiratorial narratives on twitter and instagram. We thereby combined digital methods and close reading techniques, bridging gaps between big data analytics and discourse analysis, in an approach that, following Gerbaudo (2016) could be called ‘data hermeneutics’:
By asking what verbal tools conspiracy communities use and where they got them from, it is possible to answer the question: if conspiracy theorising is a form of social critique, what critical tools do they use, how do they use them, and what kind of social critique do they make possible?
Like conspiracy theories themselves, words can connect disparate domains and communities. For example, the word ‘gaslight’ might discursively link domains such as social justice campaigning with conspiracy theorising, and the ‘woke’ left with the libertarian right. In cases like this, words are boundary objects: “objects which are both plastic enough to adapt to local needs and the constraints of the several parties employing them, yet robust enough to maintain a common identity across sites” (Star and Griesemer, 1989, p. 393).” Verbal boundary objects, such as ‘gaslight’, tend to originate from one domain and community, and get co-opted by another. This can be a powerful disinformation tactic, illustrated by the success of Donald Trump’s co-optation of the phrases “fake news” and “big lie” for his own purposes, and confusing the discursive clarity of the terms and thus its ability to critique him. By attending to how a single word or phrase moves between communities, it is possible to interrogate the tactics used by conspiracy communities and the kinds of social critique they afford.
We have identified keywords in four high level themes:
A burgeoning effect of diagonalism is the diagonalization of culture at all levels. Discussing climate change denialism, Latour (2004) pointed out how conspiratorial actors and critical theorists may have something in common: they are “similar in the structure of the explanation, in the first movement of disbelief and, then, in the wheeling of causal explanations coming out of the deep dark below”. Conspiracy thinking often co-opts arguments from media-literacy (Starbird 2017). This implies a transition from emotivistic populism to a newly-found intellectualism. Parallel but not reducible to hash-tag hijacking (whose subject and target is the a networked affective public), diagonalism has a propensity towards a ‘theory-hijacking’ from emancipatory politics: diagonal conspiratorial actors represent themselves as a colonized and dominated subjectivity, thus seeking a new power-knowledge situation. As in post-truth’s case (see previous section), these communities don’t represent themselves as subjects, not objects, of critique: they have no role in post-truth; on the contrary, they are trying to critique it. Theory-hijacking is the epistemic side of hashtag-hijacking, and it is not enacted upon matters of concern but on the schemas of their interpretation.As we can see in the diagonalism compass below (Fig. 1) the four critical keywords we analysed present a marked diagonalism, cutting across the political compass diagram. On one hand, these keywords are contested by incompatible political orientation; on the other they are mobilized by diagonal movements that seem to destabilize received analytical categories such as ‘left-’ and right-wing’ politics.
Fig. 1 Political compass of Critical Theory terminologyZooming in on a specific critical theory, namely Hegelian Dialectics, it can be argued that the democratisation or socialisation (cf. Birchall) of social or critical theory allows for its appearance in these environments. While the entire ‘critical theory’ data set within the corpora is not very substantial compared to others such as New Age, there is a conclusion to be drawn. Nearly all the closely read tweets illustrate that it’s become an instrument which is simplified and should adhere to the conspiracists confirmation bias. Images below illustrate how Hegelian Dialectics, something the German Idealist himself conceptualised differently in various of his works, is simplified to ‘thesis, antithesis, synthesis’ or ‘problem, reaction, solution’. It is synonymous with conspiratorial concepts such as mind control or brainwashing. Yet, in a more optimistic reading, what the conspiratorial subject seems to be aiming at is providing critique on power structures. The word tree below illustrates these two points: hermeneutic liberty (in red) and adoption, application of confirmation bias (in orange). The hermeneutic liberty of Hegelian Dialectic concept is prevalent in the conspiracy spaces, mostly incorporated in the right-wing narrative. Yet, it does not necessarily have to be, indicating the notion of diagonalism this overall research is concerned with. This is also noticeable in the political compass above (Fig.1).
Meaning and interpretation is guided by for both sides as lived experiences of audiences in an attempt for a claim on ‘’truth’’ where denial is central to (white privilege) and resignification to (black privilege). In terms of diagonalism during discourse the term itself has been interpreted and appropriated by left and right wing to add to their cause and paradigm, reasserting their ‘’truth’’ and opening up the discussion and battle for allocation.In short, the main takeaways and findings evolve around the basis of qualitative analysis of tweets does not often suffice to determine the political leaning of the author. This is due to the, Appropriation of ambiguity through alt-right capitalisation, but also: critique of ambiguity through historicization. Also to conclude the effect of audiences trolling the whole discourse and capitalisation of terms themselves.
Demonizing is a tool for ‘othering’, a way to create differences between somebody's own group and the opposite group. Fake news is used as a central argument by both sides of the polarized political spectrum. Any side claims to know the truth and tries to expose the lies of the other side.
The leftist narrative claims that the right wing is spreading fake news to reach certain political goals by distorting reality with unscientific polemics. The right wing narrative claims that liberals are socialist goons that create nothing of value for the society, the left only wants to destroy and ‘demonize’ political figures on the right. By using that type of narrative, the right wing is using historical anti-communist sentiments to reach the hearts of their audience. Further, the demonizing narrative of the right wing is often based on nationalism expressed in nostalgia and conservatism of a world long lost, sometimes connected to a strong anti-muslim propaganda. The most obvious difference between right and left wing is that the right wing demonizes the left with constructed lies and fake news, while the left wing is trying to demonize the right wing by pointing out the right wing's systematic use of lies and fake news. Instead of creating a common ground and ‘diagonalism’, the concept of demonizing is a tool to create strong distinction between tribes. That is possible to observe, because twitter is a platform that is mostly used by users from the USA (as seen that president trump was the most prominent and followed twitter user). It is possible that the epistemic keyword ‘demonize’ creates a certain diagonalism in different spatial contexts, as the definition of diagonalism as a concept was inspired by the strange dynamics of the protesting movement in Germany since 2015.
The term ‘woke’ was added to Oxford dictionary in 2017, according to which it refers to:
Co-hashtag analysis confirmed findings from word-tree exploration, as only one cluster around QANON emerged:The term ‘woke’ appears to be an example of a concept that originally emerged on the left but has now almost completely been taken over by the right. Instead of being ‘woke’ towards social injustices, conspiracy theorists talk about being ‘woke’ towards various conspiracies around QAnon. If the term is invoked in ways closer to its original meaning it has a negative connotation - a form of left-wing ‘virtue signaling’. If the term is used on the left, it seems to be negative too: as a way to criticize individuals or organizations that claim to be ‘woke’ but fail to do justice to it. This makes ‘woke’ an example for a term whose meaning closed down because it was diluted due to how right-wing conspiracy theorists appropriated the term.
Fig. 4 The political compass of New Age
Generally speaking, our analysis found that people express less interest in politics, and more a desire to escape (to “ascend” or “wake”) and to live beyond the mundane, which they consider being spoiled by the interference of secret organizations (NWO, Deep State, etc.), people with bad energies, that are asleep (the sheeple), or with altered frequencies.
The fourth and final sub-project focused on epistemic keywords. Against the background of a deepening ‘epistemic crisis’ (Dahlgren 2018; Zuboff 2020) where notions of knowledge and truth are increasingly contested, our assumption is that such keywords serve as a rich source for exploring the hermeneutics of online conspiracism. A small number of keywords were selected from the previously composed keyword list to explore to what extent notions of ‘diagonalism’ (Slobodian & Callison 2021) may provide fruitful perspectives for the study of conspiracy theories in online spaces. For the present research, we focused on a set of interconnected keywords serving as a heuristic for the epistemic condition (i.e. crisis) conspiracy communities perceive themselves to be in:
Tweets in our dataset reflected users’ experience of living in a state of deception, where the truth is hidden and needs to be actively uncovered.Our epistemic sub-corpora were structured as follows:
A distant reading of deception-discourse on Twitter reveals that the term is intrinsically linked to notions of epistemic crisis. Words such as ‘lies’, ‘fake (news)’, ‘conspiracy’ and ‘‘manipulation’ dominate the corpus. The concept appears integral to the prolific conspiracy narratives of QAnon, New World Order, Obamagate, deep state, and ‘plandemic’. These connections are especially apparent when looking at the most commonly used hashtags in the corpus.
Fig. 5 Wordtree for ‘deception’ An analysis of the most common bi-grams over time shows that ‘deception’ also connects to a more recent conspiracy narrative, that of the Great Reset. Labelled a “conspiracy smoothie” for its ability to mix and blend a near infinite number of critiques into one (Klein, 2020), the powerful Davos elites emerge as central actors in the deception.
Fig. 6 Rank flow diagram for ‘deception’While ‘deception’ undoubtedly seems to serve as a verbal ‘integrator’ for conspiratorial discourse, the “true” nature of this conspiracy remains highly contested. Close readings reveal that while tweets might mention conspiracy narratives they do not necessarily support them. Rather, users from different sides of the political spectrum contest each others’ notion of what the great deception -- a central phrase in the corpus --truly is. The core conflict centers on whether the deception consists of the conspiracy (e.g. widespread election fraud), or the conspiracy theory (e.g. QAnon).
Fig. 7 Conflicting tweets on the nature of “the great deception”.A closer glance at the corpus’ top tweets support the notion that the deception-concept is remarkably complex and fluid. Appropriated by a diverging set of actors with a great deal of ideological, social and cultural diversity, the idea of a great deception resonates with political movements not only across the political spectrum, but the world: The American democratic, republican and alt-right movements (#1, #3, #5, #8) as well as British progressives and conservatives (#2, #4, #10) appear alongside a Filippino human rights activist (#6), a Thai influencer (#7) and a Kenyan opposition politician (#9). More than a cohesive conspiratorial concept, then, the deception-term functions as a polyphonous rallying cry and discursive weapon in the fight against (perceived) epistemic injustice.
Fig. 8 Wordtree for ‘hidden’ Even so, while the video dominates the corpus on ‘hidden’, Covid-19 is featured only in two of the ten most retweeted tweets. The rest of the most popular tweets highlight the second discursive trait characterizing the corpus, and a feature typical to conspiracies in general: the political and others of the ‘epistemic elite’ – i.e., those with privilege regarding knowledge and power to disseminate it – purposely hiding the truth. While most top tweets, whether originating from the U.S., India, Nigeria or China, address political and government secrecy and corruption, including Obamagate (see also the keyword Uncover), this notion of distrusting not only the political but also the cultural order has prevailed in the Western culture for half-a-century (e.g., Fenster 1999). Related is the recurring phrase in the corpus that what is hidden is in fact right in front of us, all around us if we only knew how to look, ‘hidden in plain sight’. The above is exemplified in a top tweet (#5, Fig. 9) that mocks conspiracies about Hollywood and other cultural elites who are allegedly using the drug adrenochrome for satanic rites and equivalent. The tweet combines the conspiracy discourse with the humorous meme that the cartoon Simpsons has the canny ability to predict the future:
Fig. 9 Tweet about adrenochrome Finally, the keyword ‘hidden’ underlines a curious discursive battle over epistemic authority. Unsurprisingly, what is ‘hidden’ is kept from ‘us’, ‘the people’ by those in the know. While some conspiracy theories seek to elevate and legitimize particular groups as morally sound and superior (see account e.g., in Douglas 2021), the corpus shows a strong populist collectivist discourse that positions ordinary people opposite to certain elites. Yet, typical to the contemporary ‘economies of visibility’ (Banet-Weiser 2018) and ‘attention inequality’ (Zhu & Lehrman 2016), where most misinformation is spread by a handful of powerful disseminators (CCDH 2021), the most those critical of the mainstream power and knowledge institutions and elites are also a part of them. In the corpus, the ‘Plandemic’ video is often framed and shared as an investigative documentary. The two most retweeted tweets, both claiming to uncover secrets of Obamagate, are by a former Fox News journalist and a well-known actor, and the top ten includes two tweets by a doctor questioning the mainstream view on Covid-19. Arguably, this dynamics can be said to be a foundational characteristic of epistemic diagonality of conspiracies: visibility and virality attract additional, sometimes contradictory and opposing meanings.
Fig. 10 Tweets featuring examples of 'uncovering' The word tree showed that some of the most frequent words that follow ‘uncover’ include ‘truth’ and ‘conspiracy’, and that some of the most frequent words that precede ‘uncover’ include for example ‘to’ and ‘will’ which indicate that something has been, or is about to, be uncovered by someone (e.g., ‘police’ or ‘researchers’). . Zooming in on specific branches of the tree showed that ‘uncover’ was used in relation to a variety of claims including, for example, ObamaGate, PizzaGate, Trump, Big Pharma, 5G, QAnon. But the word tree also showed opposing claims including, for example, how Trump has given credence to ‘wacky’ QAnon, and further ridicule QAnon’s mission to uncover the truth. Although the latter use of the word appears to be significantly less common in the corpus, the word tree shows that the word ‘uncover’ is used by different actors who do not necessarily sympathize with the same political actors, or endorse conspiracy theories. While these observations are insufficient to draw any decisive conclusions, it nonetheless gives some valuable clues of the fluid or ‘diagonal’ use of the word.
Fig. 11 Wordtree for ‘uncover’
Fig. 12 Wordtree for "Truth'Navigating the wordtree we visualize what truth ‘is’. It is a ‘revolutionary act’, lived through with a temporality of messianic expectation: ‘the truth is coming out’. This truth-to-come covers a series of interrelated matters of concern (Latour, 2004): the ‘deep state’, ‘5G’, the ‘genocide’, ‘covid’ and ‘vaccines.
Fig. 13 Exploring the wordtree.The following wordtree composition (Fig. 14) tells a more complex narration, an almost paradoxical formula that seems to capture an hermeneutics: “there is a conspiracy to hide the truth about this conspiracy”. As we can see, the antagonized actors are the ‘deep state’ and ‘they’ (Tuters & Hagen, 2018), defined by pragmatic keywords such as ‘trying’, ‘want’, ‘plan’. Yet, ‘you can’t hide the truth’, because it is coming.
Fig. 14 Composing wordtrees.
In Fig. 15, we can see a series of pragmatic keywords such as ‘stand’, ‘fight, ‘search, ‘check content’, sketching the set of actions required when it’s ‘time’ for the ‘battle for truth’. Interestingly, post-truth appears in the overall wordtree: these conspiratorial actors recognize they are living in a post-truth media ecology. Nevertheless, these actors do not frame themselves as involved in post-truth, because ‘their regime has brought’ it. This use of post-truth may signal a diagonalization of ‘critical theory’ theory concepts blurring the line between producers and consumers of post-truth. In this sense, these communities live through an epistemic condition in which truth is hidden and post-truth is evident. Yet, post-post-truth is coming, accelerated by a networked hermeneutics that enrols actors in searching, sharing and uncovering the deception.
Fig. 15 Before and after truth.Fig. 16 is a network visualization of the co-tag network of the ‘truth’ subcorpora. Node and edge color encode the weighted degree of connectivity of the ndoses. As we can see, it’s conspiritual in content: religious and mundane entities converge in the field of concern generated by ‘covid’, ‘coronavirus’, ‘scamdemic’, ‘plandemic’. QAnon-adjacent keywords populate most of the network. #QAnon and #WW1WGA are the most frequently co-occurring hashtags, reflecting the notorious capacity for amplification that characterizes that community. It is clear that QAnon was able to drive network convergence and integration, but this primacy should not be interpreted as stability. As we can see, established QAnon matters of concern (pizzagate) are not central in the network, dethroned by a new source of conspiratorial discourse: the pandemic. This may signal a ‘diagonalization of QAnon’: while communities reassemble around a new core concern, they import the schemas of interpretation of their predecessors. Actors freshly initiated to systematic conspiratorial thinking find themselves in an ecology that provides them with a tradition of epistemic keywords and hermeneutic practices. This may signal that QAnon’s epistemic style can survive while the newsworthiness of its classic antagonists (the Clintons) fades, thus traveling to new diagonal movements. While the analysis of the sociopolitical base of those movements can be incredibly disorienting, the epistemic keyword approach may enhance the traceability of these political trajectories.
Fig. 16 Network visualizationIn sum, our analysis shows that the epistemic keywords under scrutiny tap into elements of deception: uncovering hidden truths implies that deception is taking, or has taken, place. What is more, the analysis was informed by the notion of ‘diagonalism’ (Slobodian & Callison 2021) and the findings presented above seem to indicate that the epistemic keywords explored in this sub-project are used as a discursive device employed by actors/entities across the political spectrum (see Fig. 17, below). The difference lies in who is portrayed as the deceiver(s), or put differently, whose deception or hidden plans are, or are about to be, uncovered. In summary, while these initial findings warrant further study they seem to substantiate that notions of ‘diagonalism’ (Slobodian & Callison 2021) may offer a fruitful route into a better understanding of the mutli-faceted nature of online conspiracies. Further research might take into account media effects and the problem of digital bias (see e.g. Marres 2015)
Fig. 17 Political compass of epistemic keywords
The dataset comprised ~800k Instagram posts with 4.3 million comments with the earliest post being from late 2011. We focussed only on 2020, which also happened to be by far the biggest year in the data. Posts were gathered from 66 known conspiracy influencers/accounts as well as posts containing at least one of the following 82 hashtags related to conspiracies.
"wakeupsheeple", "davidicke", "wedonotconsent", "rfidchip",
"cabal", "attilahildmann", "thestormisuponus", "markofthebeast",
"governmentlies", "wherewegoonewegoall", "hollyweirdisevil",
"idonotconsent", "event201", "fearmongering", "populationcontrol",
"nonewnormal", "saynotobillgates", "healthfreedom", "believemothers",
"gibgateskeinechance", "filmyourhospital", "weareq", "fuckbillgates",
"fucknwo", "id2020", "hisnamewassethrich", "firefauci", "truther",
"plannedemic", "widerstand2020", "plandemic2020", "billgatesisevil",
"fakevirus", "stopbillgates", "qanonarmy", "scamdemic", "arrestbillgates",
"protruth", "wearethenewsnow", "coronafake", "andrenochrome",
"coronalüge", "projectbluebeam", "outofshadows", "darktolight",
"qarmy", "bodoschiffmann", "coronalies", "givegatesnochance",
"freedomkeepers", "stop5gflorida", "betweenmeandmydoctor", "stop5gaustralia",
"medicalexemption", "reopenusa", "medicalrights", "stop5gbarcelona",
"medicalfreedomofchoice", "pizzagate", "stop5guk", "stop5gcalifornia",
"parentalrights", "georgesoros", "stop5grollout", "readtheinsert",
"stop5gitalia", "plandemic", "stop5gespana", "stop5gpennsylvania",
"stop5gcentralcoast", "informedconsent", "stop5geverywhere",
"stop5gtowers", "stop5gglobal", "stop5ginternational", "stop5ghawaii",
"stop5gtoday", "stop5gworldwide", "vaccinationchoice", "stop5gusa",
Can we detect convergence or integration in conspiracy theories, at the level of hashtag use?
We broke the dataset into three quarters (the fourth quarter did not appear complete). We manually categorized hashtags into communities. With these quarters created maps of co-hashtag occurrence using gephi, and created coloured overlays in order to try to detect convergence or integration.
In the graphs below one can see that QAnon (blue) stays remarkably stable over time, apart from the Pizzagate (purple) which grows and somewhat overlaps somewhat with communities in the top of the graph. At the top of the graphs we see the growth of Covid-related hashtags (green), which do not overlap much with QAnon, though they do with Bill Gates (red), NWO (yellow), 5G (brown) and Conspirituality (orange). Oddly Bill Gates (red) is not present in the first quarter, though he is in other levels of analysis, see below.
Fig. 1 Hashtag co-occurence networks for instagram data Q1-Q3, coloured by conspiracy tribe
As a community QAnon (blue) was remarkably stable across 2020 and its issues had relatively little to do with the pandemic. There was little integration and convergence on display in this community, except for the Pizzagate (purple) subcommunity which came increasingly to focus on pedophelia. By contrast the other communities—Bill Gates (red), NWO (yellow), 5G (brown) and Conspirituality (orange)—featured both integration and convergence leading over the course of 2020 to the emergence of what Naomi Klein has called the Great Reset conspiracy smoothie.
Fig. 3: Histogram of posts mentioning Bill Gates on Instagram in 2020
The histogram of our corpus shows an explosive increase in Instagram posts mentioning Bill Gates at the start of the Covid-pandemic. This pattern is illustrative of how Gates quickly was construed as the main agent of the pandemic by online conspiracists. Although the main conspiratorial claim - that Bill Gates has a hidden vaccine agenda - remained central over time, the content and focus of the posts, and hence the basis upon which Bill Gates was constructed as an antagonist in the posts, varied somewhat across the datasets. Overall, a close reading suggests that the top posts in Q1 emphasized Bill Gates' evil and reprehensible motives, while in Q2 the posts concentrated on portraying Bill Gates as a criminal and often called for legislative measures. In Q3 these types of allegations seem to escalate: Bill Gates is not only labeled as a criminal, pedophile monster and murderer, but as the devil or Antichrist himself. In Q4, the content appears to enter a less emotional, more ‘analytic’ stage. What is more, while Melinda and the Gates foundation are central entities in the first quarter, they all but disappear in the last three. As the pandemic progresses, ‘Gates’ becomes increasingly synonymous with Bill. Another, final key finding can be exemplified by a post that was published only a few days after the US lockdown was implemented:
This chaotic, complex post serve to illustrate how Bill Gates and the pandemic is fused together with a vast array of other conspiracy narratives: The notion that the covid vaccine is a tool for population control is connected to notions of a great reset, that climate change is a hoax, and the age-old theory of chemtrails. The post further highlights how a connection is drawn between Gates and the UN, specifically Agenda 21 for sustainable development, labelled a “hegemonic, globalist plot” against America by many conspiracists (Norton 2014). The analysis below is divided into annual quarters. Excerpts from the top 10 most-liked Instagram posts are inserted to illustrate the antagonistic discourses that surrounded Bill Gates on Instagram in 2020. Before delving into the qualitative analysis, the word trees for each quarter help illustrate the changing antagonist dynamics at an aggregate level (‘is’ was added in the last three wordtrees to increase readability):
Fig. 4: Wordtree Q1
Fig. 5: Wordtree Q2
Fig. 6: Wordtree Q3
One key feature of how Bill Gates is constructed in the first quarter of 2020 is the idea of his involvement in vaccine development as a pretext for controlling the world’s population through microchip implants:
However, the discursive construction of Bill Gates takes a new turn during this period. Here, Bill Gates is antagonized by reference to pedophilia. This is expressed in the text, or implied in accompanying hashtags:
The findings from the textual analysis could be verified with a network analysis, where we analyzed how various keywords co-occurred in the text of Instagram posts. While already being prominent in Q1, Bill Gates starts to strongly attract various Covid-19 related conspiracy theories from Q2 onwards:Fig. 8: Q2 network showing persons and conspiracy theories (Force Atlas 2). In the network in Fig. 8 edges are weighted based on co-occurrence, the size of the nodes represents the degree and the colors indicate the type of node (person vs. conspiracy theory). As you can see, Bill Gates has a very high degree and is thus very connected (second highest degree behind ‘trump’). Moreover, Fig. 8 shows how he is surrounded by various conspiracies and this connectedness with conspiracies removes Bill Gates slightly from the rest of nodes representing persons. Two main conclusions can be drawn from the observations made: the discourse in Instagram posts reveal a continuous production of Bill Gates as representing an antagonistic enemy full of self-importance and engaged in wrongful and criminal activities, and an overlap between content relating to Bill Gates and other, often anti-vaccine, conspiracy narratives. The discourse on Instagram about Bill Gates remains consistently and forcefully antagonistic throughout our corpus. The majority of the analyzed posts clearly expresses antagonism by reference to the alleged motives of Bill Gates and his wrongful, even criminal, activities which commonly relates to this alleged global vaccine agenda. Bill Gates is described as evil, mad with power, inhumane and is repeatedly connected to criminal behavior including crimes against humanity and pedophilia. Moreover, Bill Gates is constructed as the responsible mastermind of an elitist New World Order whose objective is global population control.
The second conclusion relates to the observation that many of the analyzed Instagram posts often include and merge a vast range of various conspiracy narratives, especially through an active use of seemingly unstructured hashtagging. For example, the #WWG1WGA which can be associated with QAnon (Morrish 2020), and the #WEAREFARRAKHAN which can be linked to the Nation of Islam (Mason 2021), can be observed in the posts. The posts do not necessarily push a coherent conspiracy theory, but rather various conspiracy narratives that seem to align with the notion of ‘conspiracy without theory’ as proposed by Rosenblum & Muirhead (2020). Such conspiratorial, discursive practices in online contexts may be fruitfully explored from the perspective of secondary orality in which ritualistic, repetitive performativity is a central feature (Venturini, forthcoming). Finally, some caution should be taken in interpreting this kind of online conspiracism. As has been previously reported, various actors have exploited trending hashtags in order to reach wider audiences. For example, Daesh has relied on this tactic (EUvsDisinfo 2020) and it has been discovered that QAnon hijacked #SaveTheChildren to reach new audiences after being banned on various platforms (Roose 2020). In other words, the extensive use of hashtags may in some situations thus be a mere tactic to build an audience.
Fig. 9 Word tree of Microsoft mentions in Q1
Fig. 10 Word tree of Microsoft mentions in Q2 Our textual analysis reveals that there was a prevalent focus on Bill Gates rather than Microsoft within the dataset. Microsoft is highlighted as a “partner in crime” or as a platform/resource for Gates to gain global control. One main take from the textual analysis of Microsoft mentions on Instagram is similar to the findings from the network explorations of organisations where several different spheres become intertwined. In this entanglement, Bill Gates (and Microsoft to a lesser extent) is shown to act as an integrating force. Additionally, several conspiratorial narratives within the corpus also show a clear emphasis on the pandemic, which could be argued to amplify the conspiratorial narratives of Bill Gates.
Fig. 11 Organisation Network
The most evident network convergence that characterises the transition from Q1 to Q2 is the integration between two archetypal organisations of the “covert sphere” (Melley, 2012), the FBI and the CIA, with the Big Pharma conspiracy theory (Blaskiewicz, 2013). Moreover, we can observe how in Q2 the names of pharmaceutical companies involved in vaccine research (Bayer, Pfizer, etc) start to appear. The force-directed layout we used (MultiGravity Atlas 2), and the resulting spatialization of named entity co-occurrence, shows a marked difference between the two quarters: in Q1, ‘CIA’ and ‘FBI’ occupy an antipodal position in respect to ‘big pharma; in Q2, they are strongly connected. This network dynamic reflects the acceleration of conspiratorial narratives centering on the pandemic and their ability to assemble ever-expanding conspiratorial weavings that schematize real-world events.The network analysis of the ‘Microsoft’ named entity produces similar findings. In this case we focus on the ego-network of ‘Microsoft’, including both persons and organisations. Edge weight and color encodes the weighted degree on the node. A tendency of this network is to show increasing convergence towards conspirituality (Ward & Voas, 2011): from Q1 to Q2, ‘God’ and ‘Jesus’ gain network centrality, together with ‘evil’ and ‘David Icke’. In other words, a conspiratorial networking reassembled the narratives around ‘Microsoft’, moving from the distant domain of multinational capitalism and intergovernmental organizations to the pulsating center of the conspiratorial toolkit and ‘name dropping’. Another interesting feature is the increasing network antagonism between ‘Trump’ and ‘Bill Gates’: both strongly connected to ‘God’, they seem to confront each other as the network authorities, moral figures and political options.
Fig. 12 Microsoft Ego-NetworkAs in the previous graph, the ‘Microsoft’ ego-network shows integration and convergence in which previously distant nodes are now associated by strong connections. In this case, the integration of ‘Microsoft’ in the conspiratorial network is realized by the conspiritual cluster: once the ‘God’ node is associated with ‘Bill Gates’ (reflecting increasing textual co-occurrence) a new narrative can be brought forth, producing matters of concern on a completely different scale, moving from the merely polemical to the existential. In this sense, when conspiratorial convergence is realized it’s because it is able to enrol actors from different domains. Reconfiguring the global connectivity of the collective and connective ‘cognitive mapping’ of the current epistemic crisis, convergence brings actors from difference scales and modes of existence together: when ‘CIA’ and ‘big pharma’ converge a layer of depth and secrecy is added to the hermeneutical style of conspiratorial actors. When ‘Bill Gates’ and ‘Trump’ are triangulated by ‘God’, a sense of moral and spiritual urgency feeds into the interpretation schema. While epistemic keywords tried to capture how actors collect entities to name, entity recognition reports which actors are named. In this sense, network convergence implies network expansion: while integration provides disparate and diagonal communities a common ground through the networking of shared keywords, convergence restructures global connectivity by pushing the network authorities of these communities in the foreground. In our case, convergence is mediated and promoted by the ‘God’ node. Once convergence is realized, all the chains of association from a network can be transferred to another one. Suddenly, from Q1 to Q2, ‘Microsoft’ is at the center of a story that belongs to a cosmic, religious scale.
In the following part, dominant and marginal communities/tribes in which Bill Gates is antagonized over the first nine months of 2020 on Instagram are discussed.
Fig. 13 Dominant and marginal communities around Bill Gates1. Bioweapon is the main tribe of how Bill Gates is represented on Instagram. The results indicate that Gates is depicted as a person who intends to control and depopulate the world by promoting the idea of getting the vaccine and involving in the vaccine production process. Even though no significant change was observed in the prevalence of this idea over the period of the study, users mainly targeted Gates for implementing microchips (this discussion was heated from March to June 2020). Relying on screenshots of news headlines from alt-media that covered stories about Gates's actions in India and some African tribes, users consistently accused Gates of controlling the population and creating a "New World." Amid this group, the memes and news headlines circulate to emphasize that Gates deliberates to modify human species by selectively mating people. In fact, Instagram users who fit in the bioweapon community/tribe claim Gates practices eugenics.
Fig. 14 Dominant and marginal communities over time2. In relation to the bioweapon community/tribe in which people highlight the Covid-19 vaccine as a way of governing people and shaping a new order globally, a notable group of users manifests their opposition to the vaccine by targeting Bill Gates. They do not merely claim the vaccine is made for breeding but also defend the idea that the virus is released intentionally. This group accused Gates and other people involved in making the vaccine, including Dr. Fauci, of profiting from the process. Even though the activities of anti-vaccine people initiate from the beginning of the Covid-19 outbreak, especially in the US, the debate about Bill Gates has popped up from June to September. Like the previous community/tribe we observed, using Bill Gates images with the text inside them is the most common way of maintaining him as one of the key faces in conspiracy narratives on Instagram.
Fig 15. Network of topic and user clusters
3. Among the community/tribe that accuses Gates of human rights abuses, the world's ideas of breeding and depopulation are also reproduced. Furthermore, users depict Gates as a pedophile and murder. Images shared by this community/tribe portray Gates as an evil and monster. Indeed, users implemented stereotypical facial characteristics of the demon in media to illustrate the real face of Gates that is hidden behind his seeming humanitarians' activities. Through making connections between all these stories and promoting mandatory vaccinations by Gates, this community/tribe asserts that Gates is a deceiver who intends to take the world under control. According to the graph, April and May were the heated months for this debate; however, he has constantly been a target of such allegations.4. Another community/tribe that antagonized Gates is QAnon. The supporters of this theory expressed their opposition to Bill Gates in various ways throughout the first nine months of 2020. In another way, we have not observed a significant change regarding escalating this issue over time. Moreover, QAnon includes a wide range of topics that supporters propagate; due to that, images categorized in this community/tribe are interconnected with others. The footprint of this community/tribe is clearly visible among Trumpist and anti-vaccine groups. Comparable to other categories, news headlines and memes are the most circulated images within the QAnon community/tribe. 5. To put it concisely, we placed images in 22 categories; however, they cannot all be named as a community/tribe. As the findings indicate, some categories are connected and shape the larger community that can interpret under conspiracy theory discourse on Instagram. Even though thematic dispersion among the images is significant, they do not merely belong to a specific category. Indeed, one image can point to Gates’ inhuman face and simultaneously raise the issue of depopulation. Since images do not solely indicate how Bill Gates is constructed on Instagram, textual content and hashtags also should be considered to provide a comprehensive understanding. Correspondingly, the practice of implanting a chain of hashtags to share images is a meaningful sign that shows the overlap of images themes. Interestingly, the variety of images is not as much as the themes. Clustering images in Pixplot based on the most popular hashtags evidence that similar images circulated in different communities/tribes. Mediated practices of users on making an antagonistic face from Gates through sharing images is repetitive.
Fig. 16: overview of 5 top hashtags images/ #billgates, #coronavirus, #billgatesevil, #Id2020, and #covid19
Overall, we found that conspiratorial influencers exist in a much bigger web of accounts and hashtags. The data identified a co-occurence of other conspiracies and related hashtags in the influencers’ content including 5G, satanism, Pedogate and the New World Order (NWO). The influencer accounts identified were not outliers in the network, suggesting convergence between conspiracy content on Instagram. This suggests that individuals who share conspiracy content are likely to be interested in a broad range of theories, however further analysis is necessary to determine whether they are contributing to the wider convergence of conspiracies. What we can conclude, however, is that it is difficult to sustain prominence as a conspiratorial influencer with accounts facing difficulties as content moderation systems work to reduce disinformation online.
The research focused on ‘actors and entrepreneurs’ of conspiracy theories (Venturini, forthcoming) with the aim to identify key actors in the dissemination of #TheGreatReset content on Instagram in 2020. As such, our research questions were:
Fig. 18 Fruchterman Reingold LayoutHaving explored the overall network, we chose to zoom in on individual accounts to find top users for the year of 2020 according to the following measures: ‘most posts’, ‘most likes’ and ‘most comments’. The findings are presented in the visual below: Fig. 19. Top Users for 2020
Conducting the time series analysis of the top accounts, we calculated the most influential accounts across quarters 2-4 of 2020 and discovered the following:
Presented below are the top influencers in quarters 2-4 of 2020:Fig. 20 Top Users by Quarter, 2020.
By combining insights from the top influencers in each quarter of 2020 with the top overall influencers, we identified the top five conspiratorial influencers:
Of these five accounts, we selected the 2 most prominent influencers for further analysis using qualitative and network analytical approaches, as discussed in the next section.
Fig. 22 One-step ego network of @criticalthinking101While the ego network above only gives insights into the hashtagging of @criticalthinking101, the two-step ego network below situates the user in the wider network of influencers. It shows connections of @criticalthinking101 to other users using the same hashtags in the network.
Fig. 23 Two-step ego network of @criticalthinking101
Unlike the previous user, this account is still active. perceptionreconfiguration started their account on 10th July 2020 and shares content mainly relating to the Covid-19 pandemic, but occasionally also other conspiracies such as pedogate, pizzagate and satanism. Their account is solely focused on conspiratorial content, featuring no personal posts or identifying information. They first mention The Great Reset on 10th July 2020 in a video where they show the World Economic Forum’s Great Reset initiative model and use it to make a case for covid being a ‘plandemic’.The user created a total of 53 posts between July and November 2020 using #TheGreatReset, with the hashtag often appearing alongside other popular conspiratorial hashtags (e.g. #scamdemic and #plandemic). The content showing police heavy-handedness at anti-lockdown protests was the most popular with their audience, achieving high levels of engagement. Overall, perceptionreconfiguration demonstrated an activist/leader mentality, printing posters and encouraging their followers to unite against the ‘nanny state’.
Fig. 24 One-step ego network of @perceptionreconfiguration.Some of the hashtags they used, as seen in the one-step ego-network, include: #thebiggestscamever, #justsayno, #hoaxvirus, #fuckthenewworldorder, and #wearebeingplayed. The user’s hashtagging in the network can be seen in the 2-step ego network below.
Fig. 25 Two-step ego network of @perceptionreconfiguration
Conspiracy theories are on the rise and its research has taken two major directions to deal with the spread of misinformation (Venturini, 2021). One strand deals with the computational detection of fakery and the other with interpretations of pseudo-theories. However, both miss to deal with the key features of conspiracism and their popularity. It is the very nature of for once big data and new communicative forms arising with it that rely on old and new narratives and practices. Venturini proclaims that “if online conspiracism seems hollow, it is because its core is far removed from the kind of analytic thinking we use to question it.” Our project starts with this thought that we need to rethink our methods to deal with data that - at least for us - seems messy, nonsense and random. Perhaps it is our very positionality as researchers who cannot access the field without the proper methods that shape the production of knowledge.
Hence, in our project we looked into the digital visuality of Instagram images of The Great Reset. We investigated the relationship between Venturini’s notion of digital orality to digital visuality. Venturini coins digital orality as formalised patterns of communication that are flimsy and repetitive and often appear to be mundane and hence not of - at least academic - importance. Venturini puts forward digital orality as a trope to understand conspiracy theories through their attentive structure and flagrancy. He thereby relates to McLuhan ’s (2004/1964) and Innis (1986/1950) historical approaches to understand media through their medium. Orality thereby originally referred to pre-digital ages, where culture transferred through word of mouth. Oral culture is shaped by repetitiveness and its relation to popular culture and folklore. Ong’s (1982) notion of secondary orality refers to a post-literate orality through electronic media technologies that bring back cultural practices of the past. Secondary orality is based on formalised patterns, of rites and passages that travel through communicative practices, those are easy and accessible and refer to popular culture.
Papacharissi (2015) uses the term of digital orality to show how new modalities of storytelling rely on the affordances of the digital but also referencing practices of the past. The latter relates to Jenkins (2006) work on ‘convergence culture’, namely, how new and old media collide and afford new forms of knowledge production. Papacharassi (2015) puts forward that “big data'' may not change the definition of knowledge, but they do modify how we communicate knowledge” (p.2).
The project itself is based on a large data set of 30 thousand images relating to conspiracy theories. It affords narratives of knowledge by weaving image assemblages together for understanding broader themes of conspiracy and their subsequent spaces. Our sub-project seeks to answer the following questions:
In the next section we shine a light on how to understand a large data set of images relating to the great reset. We reflect on our epistemic standpoint, the data set, and propose to bring back Law’s (2004) thought on method of assemblage to deal with ambiguous data surrounding discourses of conspiracism.
Our methodology follows Law’s (2004) criticism on social science to look for dominant narratives and to not deal with the messiness of data on that basis . He asked in 2004, a time pre-social media, how might methods deal with mess? And how to represent messiness without looking for dominant patterns and lines, but embracing its ambiguity? Hence, we argue that we need to embrace data ambiguity for understanding the complexity of digital experiences and not try to find a linear story (a similar experience even to that of an everyday social media user). Data is not as neutral and objective–methods and data do not simply describe social realities, but recreate them. D’Ignazio and Klein (2020) put forward how data visualisation always relates to power and often dismisses to deal with the unknown, the mess, the margins and peripheries.
Law (2004) calls this a “method assemblage” (Coleman & Ringrose, 2013; Lury & Wakeford, 2013). Methods do not only describe but also produce and enact the realities they seek to understand (Law, 2004). Law’s (2004) principle not to clean up data but to embrace its messiness. He argues that data should be tackled in its fluidity and multiplicity to embrace the modern experience of the world that is ambiguous and ambivalent.
Our sampling is intuitive and highlights the randomness of human intelligence, we navigated through images with the PixPlot provided by our wider team using the top hashtags that relate to the great reset (#newworldorder) while also keeping in mind our group’s division of the main theme into the subclusters Globalism, Covid-19, Technocracy and Dictatorship. From this we followed Law’s three-folded principle of crafting and bundling relations:: “(a) whatever is in-here or present (for instance a representation or an object); (b) whatever is absent but also manifest (that is, it can be seen, is described, is manifestly relevant to presence); and (c) whatever is absent but is Other because, while necessary to presence, is also hidden, repressed or uninteresting.” (Law,2004, p. 161) We crafted relations through the digital practice of clicking, zooming in and out to see what appears, and what images stick and ‘prick’ (Barthes, 1981). ‘Pricking’ of images refers to when a photograph affects one personally and elicits an immediate, visceral response. This pricking is a vulnerable experience that constructs knowledge about the viewed (Page, 2017). Through discussions and debates on what appeared to us as very present, as absent and as uninteresting to see where we meet and diverge. On the basis of this we decided on forty top images that should represent the great reset. Furthermore, we tracked narratives through a manual reverse-image search to show convergence in such that images are reconfigured and recontextualised in the digital space. Through reverse-image-search we are able to highlight how visually similar images appear in different spaces and discourses and how they are re-fabricated through reverberations in the digital space.
Furthermore, we tracked narratives through a manual reverse-image search to show convergence in such that images are reconfigured and recontextualised in the digital space. Through reverse-image-search we are able to highlight how visually similar images appear in different spaces and discourses and how they are re-fabricated through reverberations in the digital space.
Thereby, we were aware of the basis of our knowledge production. Our view is partial and constructed from a specific point of view and on the basis of specific skills. We are both researchers that identify as female, which can be an asset to understand discourses of conspiracy that are predominantly shaped by white males. Furthermore, we are both qualitative researchers with a lack of skills in digital methods, which pushed us to think more creatively of how to deal with a large data set without mining and analysing the data through digital tools and methods. The latter can be seen as a limit, however, is an important mention to show the cracks and limits of knowledge production.
Fig. 26 Top forty images compiled in the research assembled alongside some of the results of the reverse-image-search queries
Our overarching major finding is that digital visuality relates to digital orality in such a way that it is repetitive through aesthetic codes (white font, short sentences, colorful comics), is memorable (iconic images, famous people) and shocking (absurdity, war images, WW2 references, historic images).
Fig. 27 Images containing religious connotations connected to our sub-clusters of Globalism, Covid-19, Technocracy and Dictatorship and are indicative of other patterns observedOne observation which became an apparent pattern within images which contained or represented religious connotations. This assemblage of images could be further divided into subgroupings that were based on related themes, their aesthetics and narrative. Two of the most significant were based on a theme of nature or “stripping back” society back to the basics provided by religious beliefs. This is seen in references to the Garden of Eden–specifically with sin and forbidden fruit. This was observed frequently in the PixPlot in the circulation of various stock imagery related to toxicity, the government and Covid-19. On the other extreme there was a presence of influencer-esque fruit imagery which varied from advertising its purity alongside religion and conspiracy. The second is the juxtaposition of Covid-19 versus “God’s nature”. This coincides with a narrative of a religious reset that is forecast, however what is interesting is the presence of memes that contrast each other (either/or’s) based on government regulations during Covid-19. The features of digital orality that Venturini (2021) highlights in online communication as hashtags to bundle information, image templates to communicate information easily and video challenges that have a specific formalised pattern shows ritual conditions of communication. Those patterns also show in the digital visuality: the usage of meme structure and font, the use of famous people for remembrance, the use of iconic images with new writing to refer to the past and inscribe the present. As Venturini mentions, conspiratorial narratives have two crucial features that relate them to secondary orality - repeatability and memorability. Both features show in visual tropes in the great reset - similar images appear and images that prick and relate to discourses seen before. The latter we detected through reverse-image-search. Those images do not exist in a vacuum but travel through the digital web and are shaped by new experiences, thoughts and bits of information.
For further analysis, Venturini’s (2021) proposal to integrate ethnography with computational methods seems to be vital to understand attention regimes of digital orality. Furthermore, techniques of ethnography allow a deep understanding of the field site through living within it. A worthwhile analysis to undertake would be a network analysis based on our preliminary common assumptions by breaking down each theme found and visualise its trajectory and its common connectors which evolve these narratives and aesthetics which now end up monopolising social media. This would allow for a more concrete understanding of the assemblage of the great reset and surrounding conspiracies.
Our first hypothesis concerned the emergence of so-called ‘diagonalist movements’ that cut across traditional left/right distinctions (Slobodian & Callison 2021). In order to test this hypothesis, we combined ‘close’ and ‘distant’ readings of a curated list of keywords from the domains of critical theory, new age, epistemology (words related to truth and knowledge), and social justice terminology. Our analyses of the twitter data revealed a series of terms that are being pulled on by actors across the political spectrum, thus supporting the hypothesis of ‘diagonalism’.
Related to this first hypothesis, our second hypothesis was that the coronavirus pandemic was a driver behind the convergence and integration of conspiracy theories into a so-called ‘conspiracy singularity’. We tested this hypothesis by looking for evidence of convergence and integration on the level of Instagram hashtags, the co-occurrence of named entities in Instagram posts, and the analysis of images.Comparing our Twitter and Instagram datasets offers the possibility of a tentative cross platform analysis of “conspiracy theory” in the time of the pandemic. It would appear that in both Twitter and Instagram political discussions of Covid-19 are markedly diagonal. Our research into Twitter demonstrated this pattern by looking at how different communities shared abstract concepts, through using the political compass to locate different communities in a two dimensional matrix (left/right, libertarian/authoritarian). In contrast to common research practice, our approach with twitter was thus to look into posts’ content as opposed to their hashtags. On Instagram we also focussed on posts textual content as well as their visual content and their hashtags. There our findings also support the hypothesis of diagonalism in political discussions of Covid-19. Additionally we identified significant dynamism in those discussions which featured both integration and convergence leading over the course of 2020 to the emergence of what Naomi Klein has called the Great Reset conspiracy smoothie. This stood in contrast with the QAnon conspiracy theory which remained remarkably stable across 2020, its issues having relatively little to do with the pandemic.
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