First Monday

Characterizing QAnon: Analysis of YouTube comments presents new conclusions about a popular conservative conspiracy by Daniel Taninecz Miller

QAnon has become an important phenomenon in American politics due to both its relative popularity as well as its adoption/endorsement by political elites. However, this conspiracy theory/social movement has received sparse investigation in the social sciences. This gap is particularly noticeable in regards to the QAnon movement’s overall beliefs and perceptions of global affairs. This piece addresses these research gaps by using repeatable inductive computational social science methods to analyze a sample of comments from YouTube, a platform popular with QAnon followers. This investigation affirms previous observations regarding QAnon’s narratives connecting the U.S. government (particularly prominent Democrats) and alleged sexual violence against children, anti-semitism/fundamentalist Christian theology, and pro-Trump sentiments, and also reaveals several novel conclusions regarding QAnon. These novel observations include: [1] that the QAnon community sustains substantial discussion of international affairs, largely revolving around China, Russia and Israel (in order of prominence); [2] that discussion of China in QAnon comments received more “likes” than other international topics; and [3] that a nexus of conjectures tying former presidential candidate, Senator, and Secretary of State Hillary Clinton to the Chinese party-state dominate these China-centric comments. Aside from these novel conclusions regarding QAnon, this paper also seeks to make a contribution to repeatable social science analysis of YouTube comments more generally.


Research questions
Data collection
Literature review
Topic models, full corpus results
Full corpus interpretations
“Popular”/“Hyper-popular” selection results
“Popular”/“Hyper-popular” selection interpretations
International topics in the QAnon comments corpus, topic models
China comments selection results
China comments selection interpretations
Analysis of international comments
QAnon conjectural characteristics
Concluding discussion




“History forgets the moderates.” — Andrew Bird

The QAnon conspiracy theory/social movement has gained traction in the “Alt Right”, white nationalist, and broader American conservative movements, with some of its conjectures and sub-theories being mentioned and supported by prominent lawmakers and media figures (Coaston, 2020; Carter, 2018). During 2018–2019, QAnon was mentioned by U.S. President Donald Trump and numerous other high-profile individuals in several areas of American public life (Elfrink, 2019; Coaston, 2019). There is some evidence that terrorists and would-be terrorists on the far right have also found inspiration in the movement’s tenets, particularly the “deep state”, anti-Democratic Party, “Jewish World Order”, and anti-Muslim/anti-immigrant narratives imbedded within QAnon (Kelley and Hatewatch Staff, 2019). While rigorous academic research on the phenomenon is relatively scarce, observers have noted that QAnon “has been able to attract mass attention and help start a kind of social movement (called by some the ‘Trumpenproletariat’)” (Dragoš, 2019).

As minimal inductive work into QAnon-related content has occurred (possibly because of the offensive themes within QAnon), there is little consensus on what QAnon’s followers discuss, how they discuss it, what topics within the conspiracy theory/social movement are popular/unpopular, and what broad political conjectures define QAnon. This lack of analysis is perhaps most notable regarding QAnon’s international political/social worldviews, which remain wholly under-described. Repeatable, transparent, and rigorous analysis of the international content of this conspiracy theory community is sorely needed and is the primary focus of this paper.

Online platforms like YouTube play a key role in understanding communication surrounding domestic and international politics. Given YouTube’s popularity among QAnon (and the “alt-right” more broadly) as a forum for discussion, the reality that “Global governance increasingly depends on practices through which large amounts of data are created and circulated” (Fluck, 2015), and the availability and abundance of comments on the site, utilizing the YouTube comment space for social science research is warranted and is used as the data sample of QAnon for this investigation.

This inquiry posits that a replicable, inductive understanding of QAnon represents an important undertaking, especially because of the comparative scarcity of social science research on QAnon (despite its role in American political discourse). Existing analysis typically falls into either: A) network/“node” analysis concerned with which online actors are communicating with one another; and/or, B) Limited/“small-n”/non-repeatable content analysis. This paper addresses these research gaps by offering a robust and repeatable qualitative/quantitative examination of QAnon-related discussion on YouTube using topic modeling approaches.

As this study will demonstrate, QAnon is somewhat unique as a conspiracy theory/social movement not only because it combines elements of both of these political phenomena, but also because of its atypical conjectural narratives about U.S. and international politics. Aistrope and Bleiker (2018) remind us that conspiracy narratives “[...] are intrinsically linked to power relations and the production of foreign policy knowledge [emphasis mine].” This paper adopts such an understanding of conspiracies, and QAnon in particular, as potentially informative to the generation of foreign policy and international studies knowledge. It is with this foreign policy/international studies context that this paper offers the first rigorous and repeatable analysis of what QAnon followers believe in regards to global affairs.



Research questions

  1. What topics constitute the QAnon YouTube comments corpus? What concepts, policies, individuals, and social movements were most discussed in the comments?

  2. What comments on QAnon YouTube videos are the most popular (as measured by “likes”)? What do these popular comments tell us about what ideas “gain traction” in the social movement/conspiracy theory?

  3. What, if any, international relations topics or themes stand out in the comment data? What international topics are most popular?

  4. Taken together, how do the topics and popular comments within the QAnon comments corpus help to characterize the conspiracy theory/social movement?

The aim of this paper is to provide insight into the overarching topical characteristics of QAnon, with a particular focus on the international. As such, this paper forgoes formal hypotheses to better represent a naive starting point with the data and to avoid post hoc theorizing. Apart from general suspicions on the part of the researcher (due to the public reputation of QAnon), there were no formal expectations of specific topical comment content patterns when this analysis began. This approach, paired with computational social science methods, allows the researcher to “discover topics from the data, rather than assume them” (Roberts, et al., 2014).



Data collection

YouTube comments were obtained using the YouTube Data Tools’ (YTDT) Video Info and Comments Module (Rieder, 2015) [1]. This tool collects comments from the YouTube API, unnests them and records the comments along with a host of metadata (e.g., “likes”, “replies”, and timestamp variables). The comment query process involved selecting video IDs from YouTube videos, querying the comment stream using the Video Info and Comments Module, and exporting the corresponding files. These files were then modified slightly by the researcher prior to being read into R by adding a “channel” variable for all comments. Following this the files were combined into a master spreadsheet that can be read into R. The researcher took caution to not generate duplicate files, and removed missing data.

Elements of this paper’s channel and video selection were both purposive and random, so some explanation is warranted (somewhat similar selection methods, minus the unsupervised digital methods used here, can be found in Lingam and Aripin [2017] and Murthy and Sharma [2019]) [2]. Channel 2 selection was conducted utilizing previous literature on popular QAnon channels, primarily being informed by Hagen, et al. (n.d.). The Hagen, et al. research team qualitatively compiled a list of popular QAnon YouTube channels by 1) searching for QAnon on YouTube and exploring the recommended channels; and, 2) retrieving YouTube channels from high-scoring QAnon Reddit posts in the subreddits r/CBTS, r/the_great_awakening and r/The_Donald. This work resulted in a team-curated list of QAnon-salient YouTube channels, some of which were utilized in this paper. The channels “Lionel Nation” (~202,000 subscribers), “Destroying the Illusion” (~136,000 subscribers), “JustInformed Talk” (~108,000 subscribers), “Prayingmedic” (~107,000 subscribers), “Lift The Veil” (~53,000 subscribers), and “Bill Smith” (~45,000 subscribers) were included in comment querying for this paper. “TracyBeanz” (~106,000 subscribers) and “SphereBeing Alliance” (~94,000 subscribers), channels originally included in Hagen, et al. (n.d.), were excluded by the researcher for this inquiry, as they were judged to contain a large amount of unrelated content on a per-channel and per-video basis.

Following this purposive sampling (necessary because most of the YouTube “population” of videos/comments does not involve QAnon), the researcher used the Web site to generate random numbers to inform video selection. Five randomly selected videos were chosen from each channel according to the value generated using the random number generator ( allows the user to set a number range corresponding to the total number of QAnon-related videos for each channel), and comments were collected from these videos. This resulted in a data frame containing 26,821 comments generated in response to videos that featured/focused on QAnon.

In terms of data collection ethics, Reilly (2014) argues that maximally ethical best practices for the analysis of YouTube comments should remove usernames and avoid comment paraphrasing unless exact reproduction is necessary to “illustrate key themes from the dataset”. While the researcher agrees broadly with assessments arguing exact comment reproduction should be avoided if not necessary [3] to “illustrate key themes from the dataset” (Reilly, 2014), some analysis included here does include direct (but anonymized) reproduction of YouTube comments. This was done specifically because the topic modeling method used here does not produce direct quotes, and instead relies on co-occurrence of words to create a generalized summarization of latent topics within a corpus.

These model outputs effectively demonstrate aggregate topics, but are less specific concerning underlying details. For example, as will become clear later on, topic models of this corpus exhibit frequent co-occurrences of Hillary Clinton and the People’s Republic of China (PRC). In some topics, the semantic meaning of these associations is clear (as “Hillary”, “spy”, “traitor”, and “China” all occur in close association in the same topic), while a semantic meaning may be less explicit in other topics. For this reason, it can be helpful to think of these models less as objective truths about the corpus and more as tools for reading very large collections of texts. In such a conceptualization, once the broader topical themes of the discourse space are (quickly/conveniently) established with topic models, a researcher can query specific words/groups of words that are informed by these models to more directly confirm/disconfirm semantic meaning. This is the approach taken here, and as such properly anonymized direct quotations have an important role to play.




Once the tabular data was combined, it underwent cleaning/“preprocessing” (Welbers, et al., 2017), was converted into a corpus object, and finally transformed into a Quanteda document frequency matrix (DFM). This preprocessing included removing stopwords, as well as several words (generally names) related to the YouTuber responsible for making the original video. This was necessary to avoid having some prominent topics devoted simply to replies from YouTubers thanking the channel creator (names that might plausibly also refer to other prominent political/cultural figures were not removed). Conversion into a DFM allows for matrix algebra techniques to be deployed, and moves the character data to numeric values (Welbers, et al., 2017). This process preserved associated metadata and document-level variables, including comment-specific time values, while removing punctuation, and converted all letters to lower-case format. Symbols and hyperlink related syntax were also removed. Tokens (originally words) were stemmed using the SnowballC package (Bastin and Bouchet-Valat, 2014) through Quanteda.

Setting the number of topics (represented as value k) for a corpus is important as this k value represents the total number of topics requested by the researcher and is the only element of the unsupervised method set by the researcher. This inquiry began by using a series of k values (in a variety of initializations [4] and labeling outputs), examining k=5, k=10, k=14, k=50, k=55, and k=65 models in the exploratory stage of research. The researcher chose these k values to reflect current topic number ranges listed in relevant literature to assess the overall topical content at different topic number levels (Schmiedel, et al., 2018; Roberts, et al., 2018). The researcher also produced multiple k value models to assist in reading and establishing the topical characteristics of the corpus. Topic model k value estimation was then conducted using the “FindTopicsNumber” function within the LDA package (Appendix Figure 1), and the “searchK” function in the STM package (Appendix Figure 2). These estimators indicated a k value of 14 was well-fitted for the full data. Several k estimates (suggesting k=7 was well fitted) were run for smaller subsets of the data, and these are also available in the Appendix.

To limit length and repetition, summaries of all topic models are not included in this paper. As such, the recommended k=14/k=7 models were chosen to summarize this corpus/these corpus subsets, along with the “highest probability” labeling algorithm. The highest probability labeling algorithm is inferred directly from the topic-word distribution parameter, β. The researcher used this labeling algorithm for this paper, as it routinely generated only non-junk topics for all topics in the model. In other words, this configuration was least prone to constructing topics that included non-word data that remained in the corpus despite preprocessing. The results of the topic models are then presented in two ways. First, this paper presents the visualization results of the models (and references to full model word labels in the appendix). Second, this paper provides subject matter expert (SME) interpretation of the models in accordance with the literature of topic models (Schmiedel, et al., 2018). This division was judged to be appropriate to prevent conflation of modeling results with SME interpretations on the part of the reader.

The second element of this paper is similar in that it is also composed of topic modeling. However, this second inquiry focuses on “popular” and “hyper-popular” comments within the YouTube comments corpus. The researcher drew the cutoff for popular comments (admittedly somewhat arbitrarily [5]) at 10 “likes” or above. The cutoff for hyper-popular comments was drawn at 70 “likes” or above (the “popular” category thus also includes the “hyper-popular” category). These selections of “popular” and “hyper-popular” comments make up .055 percent and .006 percent of the corpus, respectively. These selections were made to inform takeaways about which opinions and comments resonated the most within the QAnon YouTube comments. Inquiry is again structured and presented in independent results and interpretation sections for these models.

One of the unexpected outcomes of this unsupervised examination of the comment data was the emergence of China as an important international relations topic within the data. As such, for reasons that will become clear, the third element of this analysis focuses on the use of topic models to examine the role of this specific topic cluster within the QAnon data. Comments remain the primary level of analysis in the China-centric section as well, and the presentation format also remains the same.

A later section of this paper (“Analysis of international comments”) utilizes a complementary but entirely different computational social science tool for analysis. This section further explores the China-related comments, but does so utilizing the key words in context (KWIC) tool from the Quanteda package in the R programming language. This package allows for a standardized and windowed “Ctrl F” search on a corpus, providing contextualized comments for SME exploration. The final section of this paper conducts KWIC analysis to explore the international perspective/worldview of QAnon and specifically comments referencing the PRC.

Broadly, this topic model and KWIC analysis is informed by Boumans and Trilling’s (2016) conceptualization establishing “counting/and dictionary”, “supervised machine learning”, and “unsupervised machine learning” as the three current methodological schemes for text analysis. They argue that these approaches should be ordered from most deductive to most inductive, respectively. This inquiry is also informed by Krippendorff’s (2004) content analysis methodology in that it attempts to ask “Which data are analyzed?”/“How are the data defined?”/“From what population are data drawn?”/“What is the relevant context?”/“What are the boundaries of the analysis?”/“What is to be measured?” Additionally, this paper’s structure was partially informed by Holsti (1969) in that it aims to describe/make inferences about the “characteristics of communications” through identifying content trend patterns, analyzing information flows, and assessing responses to communications (here, through popularity/“likes”).



Literature review

This paper is first and foremost in conversation with the limited existing body of computational social science research on QAnon. In their work on the topic of “normiefication” of fringe movements from digital to conventional media spaces, Hagen, et al. (n.d.) call for more content analysis on QAnon while establishing a list of QAnon-related YouTube channels. Regarding YouTube-based research programs in general, Murthy and Sharma (2019) note the general “dearth of literature exploring YouTube’s comment space”. Veletsianos, et al. (2018) also note the limited current research agenda on the platform during their analysis on comment sentiment as a function of presenter/presentation characteristics on YouTube. These inquiries represent the current state of the field, but also serve as a call for increased investigative work on QAnon (in Hagen, et al., n.d.), as well as YouTube comments more generally (Murthy and Sharma, 2019; Veletsianos, et al., 2018).

In part due to the relative scarcity of academic literature specific to QAnon/YouTube, research on QAnon should also be informed by broader conspiracy theory social and behavioral science literature [6]. Scholars have defined conspiracy theories as “proposed [plots] by powerful people or organizations working together in secret to accomplish some (usually sinister) goal” (Douglas and Sutton, 2008; Goertzel, 1994). Others have studied the related concept of conspiracist ideation, positing that it can be described as a belief in the existence of a ‘vast, insidious, preternaturally effective international conspiratorial network designed to perpetrate acts of the most fiendish character’” (Hofstadter, 1965).

Importantly, conspiracy theories are not necessarily false, and real information (like a sitting U.S. president being involved in planning a political burglary) has at times confirmed beliefs previously considered fringe (Bale, 2007). However, these theories’ marginalized place in public discourse does not indicate a lack of real world impact. Jolley and Douglas (2014) note, for example, that belief in anti-vaccine conspiracies by parents likely has a significant negative relationship with real rates of vaccination for children.

Regardless of underlying accuracy or actual impact on behavior, conspiracy belief systems are “notoriously resistant to falsification”, presenting what have been called “degenerating research programs” (Lakatos, 1970; Clarke, 2002). In such belief systems, new information often does not result in reassessment/disconfirmation of previous beliefs (as one might expect), but instead new layers of conspiracy are added to rationalize new problematic evidence. Goertzel (1994) argues something similar, noting that conspiracy beliefs form part of a “monological belief system”, in which a conspiratorial idea serves as evidence for other conspiracist ideation and affords believers relatively tidy explanations for contingent phenomena that are difficult to explain or threaten existing belief systems. These concepts may help explain why conspiracy theories like QAnon often seem to hold contradictory positions.

Conspiracy theories may also emerge in social groups experiencing a loss (or perceived loss) of values and social position. Laruelle (2012) writes that the Soviet middle class intelligentsia, whose social status had “fallen apart” in the dissolution of the USSR, found a “form of symbolic compensation for their loss of values, of status, and of Weltanschauung [...]” in a variety of conspiracy theories. Conspiracy theories often appear to offer a voice to individuals who feel powerless. Such theories find traction during crises and when media accounts are discovered to be erroneous or unreliable (Leman, 2007; Whitson and Galinsky, 2008).

Conceptualizations of conspiracy theories generally concur that such theories are rational (or, for Hofstadter, “coherent”) attempts to understand complex phenomena and deal with associated feelings of powerlessness (see Sanders and West, 2003). Debord (2002) notes “every major political event inevitably becomes associated with secrecy and competing attempts to explain the seemingly inexplicable.” [7] Given that conspiracy theories offer a convenient alternative to living with uncertainty (Zarefsky 1984), these explanations may help contextualize the often unorthodox assertions in QAnon comments.

The reality that conspiracist beliefs may be associated with a higher authoritarian tendency in the individual (AbalakinaPaap, et al., 1999; McHoskey, 1995) may also have utility in understanding QAnon. This association may be in part a function of the tendency among conspiracy theorists to blame outgroups for problems or crises experienced by the ingroup. Relatedly, Altemeyer (2006) argues that right-wing authoritarian individuals “have mainly copied the beliefs of the authorities in their lives” and that “fundamentalists/authoritarians do not always think illogically, [...], hold starkly contradictory ideas, act without integrity, respond dogmatically, and so on. But it is easy to find situations in which they do, compared with others [...]” (Altemeyer, 2006).

Relatedly, Hofstadter (1965) saw conspiracy theories as potentially dangerous elements of populism, presenting an interesting potential cause for a populist theory/movement adhered to by American conservatives. Indeed, much of QAnon’s discourse seems informed by the perceived threats of rapid technological and demographic change, and the movement adopts an obvious and nearly ubiquitous conversative perspective on such changes. The movement is, of course, also closely associated with and supportive of President Trump, an admittedly/allegedly conservative populist politician.

These insights are helpful, but other elements of conspiracy theory literature seem inappropriate or incorrect when applied to QAnon. Clarke’s (2007, 2002) assertions that the “hyper critical atmosphere” of the Internet will retard the development of conspiracy theories also appear to be in danger given the empirically detailed (if spurious) content of the Internet-generated and sustained QAnon worldview. Laclau’s (2005) division of conspiracy theory models into a dialectic between “the power” and “the underdog” is also problematized by QAnon, as the ultimate representative of the movement is the most powerful human being on the planet. QAnon would at least complicate such an understanding by displaying novel adaptations within the theory (the so-called “deep state”) to accommodate the reality that the heroic locus of the conspiracy is at once victimized and all-powerful [8].

Further questions may arise as to what international studies/international relations has to say about conspiracies, or, indeed, what QAnon has to say about international studies. Here, Aistrope and Bleiker’s (2018) call for a conceptualization of conspiracies as narratives that “[...] are intrinsically linked to power relations and the production of foreign policy knowledge” is instructive. Aistrope and Bleiker point out that both the fabricated/legitimized/“successful” casus belli for the U.S. war in Iraq, as well as the subsequent delegitimized conspiracies that arose in the Middle East concerning the war, are excellent case studies for the utility and importance of conspiracy theories for foreign knowledge production and policy making/justifying. They suggest such knowledge production is often part of the justification for foreign policy decisions.

Fenster (2008) suggests a similar power-perspective of conspiracy theories, noting that they can become important tools for the reallocation of power between different political actors, an effective element in political strategies, and a useful mechanism for exposing latent inequities in political-economic systems. While such altruistic and positive goals may or may not apply to this particular movement, the overall point regarding the importance for such ideas in international relations and foreign policy contexts remains.

As such, this inquiry (constructed as it is by a scholar of international studies) seeks in part to confirm/disconfirm Aistrope and Bleiker’s (2018) articulation of conspiracies vis-à-vis QAnon by examining the extent to which Trump administration policy objectives/language appear within the QAnon comment data. More simply, this work seeks to understand what the international policy priorities for QAnon might be. It follows that if insufficient rigorous study of QAnon is an overarching “gap”, sub-issues such as the international relations components/beliefs of the movement would also be lacking in research focus. Overall, while conspiracy theories have been studied in depth by psychologists/political psychologists, less work has been devoted to such theories from a policy or international studies perspective, even when the underlying conspiracy theory is [1] internationalized in concepts and subjects; and, [2] increasingly utilized by political actors to push policy goals (including international ones).

Perhaps most importantly, almost no peer-reviewed work has been done to inductively study the Internet QAnon movement on the Internet, despite the prominence of the theory in current affairs, the birth of the conspiracy on the Internet, and the strong indications that digital venues are critical to the dispersion of ideas within QAnon. This paper seeks to address this gap while operating under the assumption that the Internet is inherently international.



Topic models, full corpus results


Topic model for all comments in the corpus
Figure 1: Topic model for all comments in the corpus (Full topic label lists can be found in the Appendix).




Full corpus interpretations

The full comments corpus (n=26,821) demonstrates several interesting conclusions about the content of QAnon discussion on YouTube. For brevity, this model can be sufficiently summarized by examining its top five topics, though full topic word label lists are available in the Appendix. Topic 7 (first in prominence) is centered on words referring to children, women, sex, jews, evil, Justice Ruth Bader Ginsburg, the Supreme Court, kids, and gay marriage. This topic sets the stage for an overarching emphasis on similar ideas in the overall comment corpus. In particular, it is striking how often women/children/sex, women/sickness/evil, and Jews/Justice Ginsburg occur in close proximity. These themes also occur in other selections based on comment popularity. At around 13 percent prominence, this topic also far outweighs any other topic in the full corpus selection (the next most prominent topic coming in around eight percent of the

Topic 3 (second in prominence) is somewhat esoteric, in that there are many abstract words concerning time, love, greatness, hope, etc., but it is apparent that QAnon’s “wwg1wga” (“where we go 1, we go all”) mantra is here as well. Perhaps this topic represents the generally supportive nature of many of the comments towards the QAnon conspiracy theory/social movement and the YouTubers therein. Topic 14 (third in prominence by a slim margin) introduces another prominent theme in the data by featuring Christian symbolism such as God, Jesus, evil, Christ, lord, word, bible, etc., but also referring to the act of watch[ing] and to YouTube itself. Rounding out the topic, the concepts of power and history are also central here. Overall, Topic 14 introduces not only the religious fervor and identity of the comments, but also the close association of these beliefs and the YouTube platform.

Topic 11 (fourth in prominence) is far more secular and political. Here, Trump, money, government, results, America, whiteness and country all fall together. Alongside these terms are words about war and the military. Meanwhile, blackness, democrats, pay, and corrupt(ion) see mention in close proximity. Topic 13 (fifth in prominence) is again quite esoteric and full of abstract concepts like thought, agreement, difference, nothing/anything, but founder of Wikileaks, Julian Assange, is mentioned here.



“Popular”/“Hyper-popular” selection results


Topic model for all comments with 10 or more total likes
Figure 2: Topic model for all comments with 10 or more total “likes” (Full topic label lists can be found in the Appendix).



Topic model for all comments with 70 or more total likes
Figure 3: Topic model for all comments with 70 or more total “likes” (Full topic label lists can be found in the Appendix).




“Popular”/“Hyper-popular” selection interpretations

The “popular” comments (those with 10 or more likes, n=1,492) within the corpus differ from the full comment topics. Like the full corpus, this model can be sufficiently summarized by examining the top five topics, though full topic label lists for all the topics are available in the Appendix.

The “popular” comments model leads with topic 11 (first in prominence), which focuses on words related to evil, justice/court (likely Supreme Court Justice), Ginsburg/Ginsberg(sic)/Ruth/Bader, women, sickness, children/child, Clinton, and Jews. This topic reaffirms the importance of the “sexual abuse of children by evil prominent Democratic political figures” narrative in QAnon. In particular, Supreme Court Ruth Bader Ginsburg appears most connected by the comments to these issues in this corpus/corpus selection. This topic also includes a reference to China, the only international topic to appear in this sub-selection.

Topic 12 (second in prominence) heavily emphasizes President Trump, God, blessings, truth, family, and patriots/patriotism/country. This topic’s vocabulary affirms the Christian religious worldview of the comments, as well as the close association between President Trump and religion/God. Topic 3 (third in prominence) is esoteric, with little in the way of discernable “big picture” vocabulary outside what is likely a reference to Donald Trump (“don”) [9].

Topic 9 (fourth in prominence, but essentially tied for third with topic 3) references words like state, deep, patriots, and white, along with other words seemingly related to discussion like said, talk, info, agree, news, joke, etc. This topic reinforces our understanding of substantial discussion within the QAnon believer community of the “Deep State” and associated issues, though this time notably in “popular” comments. This topic may also indicate a reference to white (caucasian) ethnicity. Topic 5 (fifth in prominence) is also interesting in that it seems to contain vocabulary focused on praying/prayer, watch/watching (presumably YouTube), encouragement to keep up the work (presumably on the part of QAnon YouTubers), while also mentioning the President of the United States and the media.

Other notable topic contents within the “popular” selection are further references to: Christian concepts and American politics (Topic 7, seventh in prominence); war, history, “maga”, “wwg1wga”, mainstream media, fake news/“drops” (QAnon slang for information releases from “Q”), Hillary Clinton and the mainstream media (Topic 4, eighth in prominence); a nexus of terms connecting satan, the Democrats, and the concepts of home, a wall, and God (Topic 6, tenth in prominence); gay/straight sexuality, children, and sex (Topic 10, eleventh in prominence); and the Bohemian Grove, Hollywood, children, pedophiles, and former Supreme Court Justice Antonin Scalia (Topic 2, twelfth in prominence). These less prominent topics clearly still provide value in supporting an understanding of QAnon (and “popular” comments within that online community) that emphasizes/supports Christianity, President Trump, non-traditional media, a belief in an organized conspiracy to sexually assault children at the highest levels of the government and media, and perhaps conservative/anti-immigrant views of the home/the nation. Likewise, “popular” comments in this corpus also indicate a distrust of Democrats and the “mainstream media”.

The increased focus on international politics represents a marked difference among the “hyper-popular” comments (70+ “likes”, n=179) and other corpus selections. Donald Trump’s interactions with the PRC is particularly evident in topic 2 (first in prominence), while Israelis are mentioned in topic 5 (third in prominence). It appears that the most popular comments (those with more than 70 “likes”) reference international affairs, particularly related to China, more than less popular comments (China does, of course, also appear as a term in the most prominent topic of the 10+ “likes” corpus selection as well).

Similar to other topics in previous selections, Topic 1 (second in prominence) has vocabulary largely centered on Christianity, religion, country/patriotism, and security. Other words without obvious semantic significance (e.g., “watch”, “thanks”, “soon”, “late”) are also fairly common in this topic. This topic again demonstrates the nexus between Christian faith/values and patriotic American identity in the comments. Topic 5 (third in prominence) is more esoteric and hard to interpret. Death, the state, Israel, democrats, control, welfare, (political?) parties, and the media all make an appearance here.

Topic 3 (fourth in prominence, but essentially tied for third) contains words related to patriotism/patriots, “wwg1wga”, Supreme Court Justice Ruth Bader Ginsburg, the Supreme Court itself, disgust, and references to “old” and “woman” and “children” and “Ruth” in close proximity. This topic appears to reinforce the connection between Ginsburg, the Supreme Court, and child abuse mentioned in other topics from previous corpus selections. Topic 6 (fifth in prominence, but essentially tied for third) is seemingly similar to topic 3, with Ruth Bader Ginsburg and “women”/“mothers” occurring alongside references to witches, communism, rats, Satan, and Democrats.

Topic 4 (sixth in prominence) is somewhat similar to topic 5 in that it is slightly more esoteric and difficult to interpret. This may derive from the fact that some of the core words in the topic are more devoted to broad world-ordering concepts and emotions like “evil”, “love”, “group”, “hate”, and “world”. However, it is important to note that “Don”, “children”, and “parents” are all included in this topic, providing connection to both QAnon’s politician of preference and its core conjecture regarding the safety and importance of children and perhaps families. Topic 7 rounds out the topics with a relatively uninteresting collection of words regarding YouTube, religious blessing, and economics.



International topics in the QAnon comments corpus, topic models

The sample of QAnon YouTube comments analyzed contains several topical surprises. While less explicit than some of the other topics in the corpus, the several mid-tier (eighth-ninth in prominence) international relations topics stand out as unexplored in a QAnon context. QAnon is not typically discussed as a conspiracy theory/social movement relating to international relations. Several of these international terms, particularly references to China, stand out as prominent topics in the 10+ and 70+ “likes” categories. This is notable as “likes” can be reasonably equated to resonance within QAnon. It is curious that China and, to a lesser extent, Israel, are more prominent topics/more prominent “popular” topics in the corpus than Russia, despite collusion/collaboration between the Russian Federation and the Trump Administration constituting a multi-year headline-dominating political scandal in the United States.

Topics in the comments regarding faith, child sexual abuse, and fringe theories about prominent Democratic government officials are surprising and disturbing, but have been more well-documented in relation to QAnon than beliefs about international relations topics. Indeed, in a corpus of comments derived from a domestic U.S. conspiracy theory/social movement, topic model results stressing actors in the international system is worth further exploration, as the international relations perspective of QAnon is both unanticipated and unexplored.

By utilizing the full topic labels for the full corpus model (Figure 1), it is clear that topic 10 (eighth in prominence) and topic 9 (ninth in prominence) contain references to states in the international system (full topic labels are available in the Appendix). These references constitute the only inclusion of international states, events, or actors in any of the full topic labels in the corpus (and serve as the only topical departure in a dataset otherwise entirely focused on domestic U.S. concepts, individuals, parties, etc). Within these topics, we can see Israel falling as word 9 in topic 9, Russia falling as word 18 in topic 10, and China falling as word 11 in topic 10. In the overall corpus references to China/Chinese, Russia/Russians, and Israel/Israeli/Israelis/Israelites occur in distinct comments 285, 255, and 239 times, respectively. Despite the large role anti-semitic comments appear to play in the YouTube comments, as well as the well-publicized and long-running media coverage of Trump campaign/Trump administration connections with the Russian Federation, China appears to be a more prominent topic of discussion for QAnon (at least in this sample).

When looking at a model of only the comments receiving 10 or more “likes” (n=1,492), China stands as a much more prominent element in topic models of the corpus. Here (Figure 2), China is the tenth word in topic 11 (first in prominence), and co-occurs alongside words related to Supreme Court Justice Ruth Bader Ginsburg; the concepts of evil/old age/sickness; and references to Jews, children, and the Clintons. In the “hyper-popular” selection of comments (70 or more “likes”) China emerges as the third most prominent word in the most prominent topic in the topic model (Figure 3). In this topic (topic 2), China/Chinese co-occur alongside references to President Trump and Hillary Clinton (subject matter expert review of this selection of comments suggests that some QAnon followers believe Clinton to be a Chinese spy, or to have employed Chinese spies in the past). In these sub-selections of only “popular”/“hyper-popular” comments from the full corpus, references to Israel and Russia disappear entirely and are not components of any topics in the popular/hyper-popular selection.

With the topical importance of China in the corpus well-demonstrated, topic models can also be run on selected comments that feature that country. These models are specifically not run on the full corpus, but instead are conducted on a sub-selection of the YouTube comments that reference China/Chinese people. When comments in the YouTube corpus refer to China, several distinct topical associations emerge.



China comments selection results


Topic model for all comments referencing China
Figure 4: Topic model for all comments referencing China (Full topic label lists can be found in the Appendix).




China comments selection interpretations

Perhaps the most striking repeated feature of this model is the appearance of references to Hillary Clinton in 4 out of 7 of the topics. Hillary, Hilary (sic), “hillderbeast”, and “hrc” are all terms that feature in this output. References to Donald Trump appear to be the only terms featured in this selection more than Clinton (excluding references to China, for obvious reasons). Topic 7 (first in prominence, and by far the most significant topic in this model) demonstrates co-occurrence patterns between Hillary Clinton, “secrets”, the military, money, servers, and e-mails. Topic 2 (second in prominence) shows similar but perhaps more explicit co-occurrence associations between Hillary Clinton and China/Chinese, agents, spies, computers/hacking, and Diane Feinstein. Topic 3 (fourth in prominence) features China/Chinese, Google, emails, (Ted?) Lieu, traitors, and “hrc”. Finally, topic 4 (sixth in prominence) features both China and Israel, as well as America, Russia, Jews, god, country, south/black (potentially a reference to African Americans in the U.S. South), “hillderbeast”, and death. Clinton, along with prominent Democratic leaders Lieu and Feinstein, are heavily connected to China in this model of comments that include references to China. Moreover, these topics paint a picture of a nexus of beliefs about Clinton, China, spying/espionage, hacking, money, servers/e-mails, the military, and possibly traitorous behavior (presumably towards the United States).



Analysis of international comments

While topic models can elucidate broad trends in large corpora, it is also instructive to examine the data at the comment level (and thus use the topic models as tools for reading large collections of text). This qualitative examination can lend/detract support or modify conclusions presented in the unsupervised models. The previous full-corpus models demonstrate that we should focus our comment survey on President Trump, Hillary Clinton, server/email-related words, secrets/spying/intelligence-related words, discussion of China/Russia/the U.S., the concept of evil, and discussion of Jews and/or African Americans in connection with China/Russia/the U.S./Ted Lieu/Diane Feinstein/Hillary Clinton.

However, further topic modeling of popular comments shows the largest proportion of international relations topics in this corpus reference the PRC. Indeed, China’s role in the corpus as a function of positive feedback, resonance, and “traction” is quite large. After adjusting for the popularity of comments by subsetting the corpus based on number of “likes”, the significant role of China in discussions within the corpus emerges. Comments with 10+ “likes” featured China/Chinese 23 unique times, while Israel/Israeli/Israelis/Israelites and Russia/Russians were included in only nine comments with 10+ “likes”, respectively. Comments with 70+ “likes” featured China/Chinese nine unique times, while China/Chinese nine unique times, while Israel/Israeli/Israelis/Israelites and Russia/Russians were included in only one comment each. It would appear that China was referenced more often in comments that gained “traction” within this sample, while Israel and Russia occupied a more marginal place in the corpus when adjusting for popularity.

Since topic models and comment counts indicate the PRC is the most prominent international topic in the corpus, and since the presence of this (and any international topic) in this corpus is unexpected, this final analytical section will utilize the keywords in context (KWIC [10]) analysis tool native to the Quanteda package in R (Benoit, et al., 2018), to view the comment context “window” around usages of the word “China”/“Chinese” in the data. This “window” can be set by the researcher to any number of characters, including a limit large enough to include entire comments. As such, KWIC functions as something akin to a “Ctrl-F” feature, but it produces an html output that can be saved by the user, reviewed, and hosted for third party review. Using KWIC, a more detailed picture of the nexus of beliefs surrounding China in the QAnon discourse appears.

KWIC analysis perhaps unsurprisingly shows Donald Trump occupies a prominent place in QAnon discussion involving China. This is largely to be expected, as QAnon and Trump have been closely associated in the public sphere for some time, and because the movement emerged in part to defend the actions of the President as part of a greater plan. Additionally, Trump’s “trade war” with the PRC has continually been in the news for much of his administration. Interestingly, neither the “trade war” nor “tariffs” appear to be substantial topics of discussion in the data. The former appears four times, and the latter appears just once in China-related comments.

However, more nuanced elements of the relationship between the U.S. and the PRC are often discussed in tandem with 5G technology. The 289 comments referencing China include 5G 18 times, often referencing President Trump’s interest in the technology, China’s advanced level of 5G, and speculation on the dangers of this technology. Bizarrely, some comments also connect Christian theology to Chinese and American 5G technology.

Trump is going to use what is called God’s frequency. That is why he wants to develop 5G here in the United states. The frequency that China wants to use is what is called Satan’s 5G frequency. There is a difference between the two. [Comment 1.0]

It is also worth noting that a small number of the comments featuring both Trump and China appear critical of the President. Of the 62 China-related comments that feature “Trump”, six feature language that is critical of him. Many of these comments derive their criticism from conjecture that Trump is compromised by a number of powerful Jewish/Israeli actors.

Trump is doing for Israel, Trump saves 3 Black kids from China ... what has Trump done for the genocided WHite farmers of SOuth Africa? He can address the situation. Nothing. This Trump is a god damned FRAUD! Less evil than Obama and Valerie Jarrett perhaps but just as dangerous because he is part of ZOG. SO is Britain ! Ran by ZOG. [11] [Comment 1.1]

While such comments do not constitute a large proportion of the comments corpus, they do represent a proportionally larger share of the comments than those on the “trade war”.

The concept of moral evil appears multiple times in comments that also reference China. As with comment 1.1, many of these comments seem to refer to a cabal of various actors, typically Jewish/Israeli, who are working/have worked to undermine the United States. Many of these comments also refer to some variation of “the evils of Communism” and decry the growing power of the PRC. Several comments note a number of prominent Democrats as evil, including President Obama and Hillary Clinton. QAnon followers are also concerned that Clinton’s e-mail server hack represents an evil/nefarious connection with China.

The nexus of topics connecting China and Hillary Clinton in QAnon YouTube comments dominates the China comments, a fact somewhat reflected by the previous topic model outputs shown in this paper. However, exploring this connection further using KWICs reveals that comments featuring China demonstrate a propensity to connect Clinton’s political past, her e-mail server, and potential treasonous behavior involving U.S. military secrets, while also directly calling for her death. Several examples below provide support for the topic models and indicate that many QAnon followers believe Clinton to be a Chinese spy:

Yes Hillary is a Chinese spy!! It will be proven!! [Comment 1.2] [12]

The difference is that Hillary actually does work for China. Trump doesn’t work for Russia. That’s what makes one instance a joke and the other serious. [Comment 1.3]

Also as first lady Hillary and Bill gave China MFNS. Irrevocable. Gave them military hardware blueprints and top secret intelligence all awhile dumping all cia field agents causing many to be murdered and imprisoned worldwide. I remember the 90s. They are traitors. The media was so bs covering their deeds. [Comment 1.4]

Interestingly, these comments suggest that QAnon appears to posit a mirror image of allegations of corruption against the Trump campaign onto Hillary Clinton/President Bill Clinton/Hillary Clinton’s presidential campaign, while substituting the Russian Federation for the PRC. Attacks against “the media” are also drawn into this comment type, which also contains elements of so-called “whataboutism” (Kurtzleben, 2017; Sullivan, 2017). These conjectures of corruption, spying, and betrayal of the United States are reflected by the China-specific topic modeling previously described.

Previous topic models also appear to capture both heavy emphasis on Christian theology in the full corpus, as well as strong topical representation of both China and Hillary Clinton (in both full and selected corpora). However, less explicit in the previous models is the nexus of beliefs connecting Clinton, China, and Christian theological concepts to one another.

So what if Hillary is the women riding the beast in revelations the one the kings of the world get involved with and has to drink her cup. (if I could remember how to spell right now this would be worded different) now what does it mean come out of her my people and who is the great deceiver? If Hillary is the the Harlot? And what is the dragon/beast??? China??? I am not sure but some things are adding up some!! [Comment 1.5]

Hillary is a pedophile a child Trafficker a Terrorist ... She and Bill gave away shit to China Sold stuff to RUSSIA ... Hillary and billy drug dealers ... oh but people play her OPINIONS like she is someone .... In thye name of JESUS ... STOP STOP Feeding this evil witch .... [Comment 1.6]

Of course Hitlary is in the bag for CHINA!! She IS the DEVILS best bitch!!!! Make her Swing!!! Make her Swing!! [Comment 1.7]

These comments demonstrate a clear nexus between biblical millennialism, Clinton, and China. Moreover, our topic model outputs also find support in more emphasis on sexual violence against children, though specific comment analysis expands this to include Hillary Clinton as a perpetrator of such activity (other comments suggest Clinton has been involved in organ harvesting in the PRC as well).

Finally, specific comments are valuable in that they confirm the seemingly violent nature of the topics contained in the earlier models shown in this paper. Numerous comments referencing China suggest Hillary Clinton should be assassinated and/or executed without trial.

Hillary is really out of options to avoid military execution for child trafficking and such and such ... She got no friends left but maybe China ... Listen to HRC China, she’s got a good idea for you. But is Hillary saying that hacking the DOJ is possible??? Or that it is desirable and legal??? She once had security clearance??? WOW ... Really Q is right ... These people are stupid!!! Thank God an outsider got to kick them out!!! Retarded ... [Comment 1.8]

poetic justice ... hang Hillary with rope Made in China [Comment 1.9]



These KWIC outputs demonstrate fine-grained support for our topic model conclusions, but also more accurately convey the violence and anger within many of the QAnon comments. In this sample, QAnon YouTube comments demonstrate a series of beliefs connecting Hillary Clinton to various treasonous activities involving China, as well as biblical connotations and conjectures that she is involved in sexual violence against children. They also demonstrate a general animus to Clinton personally, calling for her death on numerous occasions. Overall, 131 of 289 comments that feature China also featured a reference to Hillary Clinton (in one form or another). These comments frequently reference various types of traitorous behavior to the U.S. and/or noted that there was a connection between “her” e-mail server and China.



QAnon conjectural characteristics

Utilizing these topics and topic interpretations, we can observe several characteristic conjectures within QAnon:

  1. A worldview that posits high-level individuals within the U.S. government and the media are involved in sexual violence, likely against children. An overall focus on the Supreme Court is also apparent (with similar undertones).

  2. A worldview inclusive of Christian theology, imagery, and symbolism. A close association between Christian concepts and patriotism. A close association between Christian concepts and YouTube. A close association between Christian concepts and anti-semitism.

  3. Political support for President Donald Trump, and an association between Trump, American identity, and Christianity.

  4. An emphasis on unity and in-group cohesion on the road to the truth. [13]

  5. An apparent emphasis on vaccines and possible (international?) political conspiracies around vaccinations.

  6. Topic models and comment word counts indicate the People’s Republic of China is likely the most prominent international topic for QAnon.

  7. PRC topics are closely paired with discussion of Hillary Clinton, and is often framed in Christian/millennialist terms. Hillary Clinton’s alleged espionage ties with China outrank both the “trade war” and Trump Administration tariffs on China in importance for QAnon.



Concluding discussion

Several conclusions related to conspiracy theory studies present themselves from examination of the QAnon data. The corpus analyzed here does not provide evidence that the oppositional, strident, and often verbally violent content within QAnon has matured, adding nuance to Laclau’s (2005) assessment that conspiracies revolve around divisions between “the underdog” and the community “in power”. Given the reality that QAnon as a movement has emerged/become popular during the presidency of the politician it supports, the movement’s continued animus toward “the powers that be”/“the deep state” can be interpreted as an example of what happens when a conspiracy movement finds its focal point in the halls of political power. Instead of adapting or evolving into an understanding of President Trump as a powerful person, QAnon commenters seem more inclined to create new reasons for why he remains an underdog. As such, the popular demand within a conspiracy theory to challenge the social order and gain power seems durable to actual gains in that political power (Yablokov, 2015).

This corpus indicates that the demand for challenge/power acquisition has not been mediated in this case by gaining immense, and for several years essentially unrivaled, structural power in the U.S. government. All of this is to say that a “Laclauian” conceptualization of power vis-à-vis conspiracies is agnostic to actual power gained. Even when power gain is immense, little may change in the ideation of the conspiracy theory.

QAnon suggests the continual search for clandestine actors to blame for social/political ills is best conceptualized as a “moving the goalposts” characteristic, as it still occurs when all available scapegoats are out of political power. While much more research is needed to suggest a generalizable trend that might apply outside of QAnon, it is possible several things may be occurring at once.

First, previous literature reviewed in this work (e.g., Altemeyer) suggests there may be some connection between conservative/authoritarian mindsets and identity movements that predisposes individuals to such conceptual “moving the goalposts”, since these individuals simply look to receive new beliefs from authorities (no matter the content). Some of these individuals may have come to rely on YouTubers/YouTube channel hosts as such authorities.

Second, the peculiarities of information on the Internet may also be partly to blame, as individuals are/may perceive they are under a more constant bombardment of facts, events, personalities, etc. Such a phenomenon would align with Fluck’s (2015) view that the highly contingent and uncertain global system, often presented to people via online platforms, makes a monologic conspiracy both appealing and comforting to some people.

Whatever the underlying cause of this iterative “moving of the goalposts” in search of a new all-powerful enemy (despite political allies holding power), other elements of conspiracy theory literature seem inappropriate or incorrect after an examination of the QAnon phenomenon. QAnon comments appear to strongly counter Clarke’s (2007, 2002) assertions that the “hyper critical atmosphere” of the Internet will retard the development of conspiracy theories through discouraging believers from articulating explicit details/evidence. The empirically inaccurate but fervent/deep evidentiary detail of the QAnon comments examined here strongly suggests this concept is mistaken. Indeed, the evidence examined here suggests the opposite trend has occurred, at least regarding QAnon. The QAnon research program may indeed be “non-falsifiable” and somewhat immune to self-contradiction, but the Internet is likely increasing the speed at which such a “degenerating research program” can be constructed/maintained/modified (thus making Clarke half correct).

QAnon’s thriving and popular YouTube community further problematizes Clarke’s idea that:

“As long as there are ways in which the received view is less than perfect, this activity can proceed and internet conspiracy theorists can remain active. However, in and of itself this activity cannot be sufficient to overthrow a received view in favour of a conspiracy theory. The most it can do is cause people to suspend judgement. Before we can reasonably expect a conspiracy theory to replace a received view, that conspiracy theory must be judged to provide a superior explanation of the relevant phenomena than the received view.”

First, the comments and models examined above indicate that QAnon commenters are not merely “suspending judgement”. There is far too much (empirically baseless) theory building to reduce QAnon ideation to this. Second, QAnon makes supporting this perspective difficult as the conspiracy fully replacing orthodox political or international relations views for the majority of society is not the only issue at hand. Obviously, the evidence for much (all?) of what QAnon posits is lacking, and for this reason many people will reject it. Nonetheless, QAnon’s popularity does contribute to the political discussion, as it produces an extreme-right wing perspective with its own internally coherent empiricism and epistemology.

One is struck reading QAnon YouTube comments at the fervor and belief commenters give these YouTube videos, and it is important to note that if YouTube view counts are any indication, such beliefs are subscribed to by at least hundreds of thousands (likely millions) of people. As such, QAnon shifts the conversation, or the “Overton Window” of what is possible, real, and politically viable (Lehman, 2012). Simply put, its mass adoption, or lack thereof, is not necessary for it to have a substantial polarizing effect on the spectrum of American political thought.

As such, this paper supports an opinion more akin to Drezner’s (2010) view that “[...] it’s not that the Internet creates paranoid or conspiratorial views. The World Wide Web simply allows like-minded extremists separated by geography to form their own online cocoon.” As indicated by our analysis of popular comments, the forum of YouTube allows for a normalization of fringe ideas into a countervailing, non-empirical worldview that must be accounted for. If culture is indeed an “aggregate of beliefs and ideologies that stimulate action” (Adams and Roscigno, 2005), and not a first-past-the-post, winner-take-all scenario, the fervor, detail and internal coherence of QAnon’s belief system must be a great concern to policy-makers and the general American public. Given the fecundity of the YouTube QAnon content creation environment, the theory does not need to “win over” a majority or plurality of Americans to create a distinct political community with its own news sources and beliefs about politics/international politics.

Interestingly, QAnon is both overtly aligned with massive political power and yet remains largely a fringe American political perspective. QAnon foreign policy/international relations beliefs may be even more marginalized, as this author (someone hopefully well-informed regarding QAnon) was unaware the conspiracy had international relations beliefs at all before this study began. As such, while in some ways QAnon believers can be conceptualized as the most “pro-Trump” individuals in the country (and thus highly proximal to political power, at least ideologically), they/their ideas are also 1) either largely unknown to the general public, and/or, 2) almost entirely ostracized from legitimacy due to the extreme nature of their beliefs. In this circumstance, ideological proximity to power is not a source for legitimacy for the QAnon movement, particularly in regards to foreign policy. Indeed, despite descriptions and references from the White House using the language of QAnon, this credibility gap persists.

Such a credibility gap is even more acute in relation to international issues. Topic models and comment word counts indicate the PRC is the most prominent international topic in the corpus, and connect former Senator, Secretary of State, and Democratic presidential candidate Hillary Clinton (as well as her husband) intimately to various real/imagined foreign policy disasters related to the PRC. Here again Aistrope and Bleiker appear half correct, as this corpus indicates a substantial amount of “narratives” and “modes of knowledge production” related to international affairs. However, the legitimization that is theorized to follow such narrative building (thanks to proximity/alignment with political power) is lacking, as a “QAnon China policy” perspective is not widely-accepted.

Beyond the window of QAnon’s conjectures and patterns of belief, this case study also produces wider take-aways regarding the global system. In particular, QAnon demonstrates that while the global order is increasingly dependent on “big data” generation and utilization, some subset of individuals are less inclined to find rational utility in either the breadth or availability of such information.

Instead, the international relations topics within this corpus demonstrate that many popular conjectures within QAnon are concerned with foreign affairs in the same “monological”/“non-falsifiable” way as domestic affairs. This agrees with Fluck’s (2015) assessment that “At the level of the existential dimension of modernity, conspiracy theorising serves the same consoling function as does technical knowledge [...]; a world free from contingency and uncertainty is an appealing one to modern individuals, who are increasingly at the mercy of distant and obscure structures” [emphasis mine]. QAnon commenter’s focus on a posited nexus of beliefs connecting Hillary Clinton and the PRC, along with a host of other political phenomena, demonstrates just such an appeal. QAnon may indicate that issues of an international nature may be particularly prone to monological conspiracization as people feel a vulnerability to outside foreign actors. There are a host of future research questions in this vein, as European/American views of China have a longstanding tradition of orientalized “othering” while some also blame China for economic damage.

Of course, this paper also has a host of limitations, primarily due to mundane restrictions on the researcher. First and foremost, with additional time and funding, a larger sample of QAnon comments could be aggregated. While there is little in the way of best practices for sampling in comment-based research, in general larger samples are always better. Methodologically, further exploration is also needed into the degree that YouTube QAnon comments (and China-centric comments specifically) are produced by bots and/or state sponsored accounts. State support for right-wing comments on Twitter has been detailed elsewhere (Miller, 2019; Woolley and Howard, 2016), and Al-Rawi, et al. (2019) note that QAnon has been in the past a popular topic of discussion for bots. Al-Rawi, et al. found that QAnon was a prominent hashtag used by bots on the platform. Such exploration of automated comments related to QAnon’s actual footprint on YouTube in terms of real human commenters, and also provides an area of further exploration regarding popularity metrics (e.g., “likes” for human-generated content versus bot-generated content). Additional examination of YouTube video transcripts in relation to attached comments would also provide an avenue of further research into QAnon online.

Setting aside “big picture” academic conversations, as well as inherent methodological limitations, this study affirms several previous conclusions about QAnon’s conjectural characteristics. QAnon comments contain a continuation and modification of previous “far right” conjectures that posit a wide-ranging, internationalized connection between an evil U.S. government (particularly prominent Democrats) and sexual violence against children. QAnon comments contain prominent topics dominated by both anti-semitic language as well as Christian theology and imagery, and this Christian language is tied closely to President Trump and American patriotism. Additionally, for the first time, we see that QAnon comments do in fact contain substantial discussion of international affairs, and this international discussion revolves heavily around China, Russia and Israel, in that order of prominence. Discussion of China in the QAnon comments received more “likes” than other international topics, and these comments are dominated by a nexus of conjectures tying Hillary Clinton to the Chinese party-state (with the “trade war” and Trump Administration tariffs on China taking a “backseat” to Clinton in importance) for QAnon.

These characteristics modify our understanding of QAnon and that movement’s presence online, and open up a host of new important research questions for social scientists interested in conspiracies, the role of religion in American political life, the current political paradigm of extreme partisanship, the interaction between the internet and ideas of truth, the role of conspiracies in international affairs, and those interested more simply in the study of QAnon itself. End of article


About the author

Dan Taninecz Miller received his Ph.D. from the Jackson School of International Studies (JSIS) at the University of Washington. He also holds a Master’s degree from JSIS and a B.A. in political science and international studies from Guilford College. Dan’s research interests focus on applying computational social science tools to large corpora of mixed qualitative-quantitative data, and he has conducted research on Russian electoral disinformation and China’s outbound investment policies. Outside of his academic work he is a data scientist/big data engineer with the Jacobs Engineering Group working on a DARPA research project.
E-mail: taninecz [at] uw [dot] edu



1. YTDT was written and is maintained by Dr. Bernhard Rieder, Associate Professor of the University of Amsterdam and a researcher at the Digital Methods Initiative (DMI). The full suite of tools is available at, “Video Info and Comments.” Source code for YTDT can be found at:

2. Examples of typical ethnographic methods being utilized on YouTube comments can be found in Lange (2007).

3. A strict/maximal ethical stance noted by Reilly to go “far beyond conventional approaches.”

4. These models were informed by STM’s “k=0M” functionality that uses Lee and MimnoM’s (2014) t-SNE/anchor words algorithm, along with the spectral initialization, to construct plausible k values for a given data space size (note however the STM package stresses this is not a “correct” k initialization, merely one that is well-fitted to the data space). After initial modeling and comparison, the researcher chose to exclusively use the “spectral” initialization recommended by the STM package vignette as it (in general) outperforms both Latent Dirichlet Allocation via collapsed Gibbs sampling as well as random initialization (Roberts, et al., 2018).

5. While numerous papers, particularly in the medical sciences, have dealt with the popularity of YouTube videos as measured by “likes”, the researcher is unaware of such work using “likes” as a metric for YouTube comments. For research that has incorporated “likes” as a measure of video popularity, see Oksanen, et al. (2015) and Kelly-Hedrick, et al. (2018).

6. Conspiracy theory studies also produce another more mundane/methodological grounding for this inquiry in that there is a call in that literature for qualitative study of such theories. Swami, et al., (2011) suggest “The main limitations of the two [quantitative] studies reported here (Swami, et al., 2011) are the correlational design, which means that causal relations cannot be clarified and the nonrandomized samples, which means that results can only be generalized with caution. [...] Future research would also do well to more explicitly understand the context in which conspiracy theories arise; a task that may be more suited to qualitative research methods. Doing so will undoubtedly provide a more rounded picture of the functions that conspiracy theories serve as well as their effects [emphasis mine].”

7. Further analysis of the QAnon topic might also explore whether or not this desire to “explain the inexplicable” is related to the voluminous evidence suggesting that the Trump candidacy/administration cooperated with the United States’ traditional geopolitical rival state.

8. This paradox reminds the researcher of Umberto Eco’s essay “Ur-fascism”, where he succinctly states that Fascist states produce “by a continuous shifting of rhetorical focus” enemies that are “at the same time too strong and too weak” (Eco, 1995).

9. While words like “really”, “said”, and “made” are all possible candidates for exclusion from the corpus as stopwords, this paper opted for as conservative a word removal procedure as possible to preserve the underlying data.

10. KWIC is similar to a much older concept credited to Hans Peter Luhn. See C.D. Manning and H. Schütze, 1999. Foundations of statistical natural language processing. Cambridge, Mass.: MIT Press.

11. “ZOG” is a white supremacist abbreviation for “Zionist occupation government”, “Zionist occupational government”, or “Zionist-occupied government”. The term is generally used to describe governments (outside of Israel) that have been “taken over” by a supposed global group of powerful Jewish individuals.

12. Comments are included with original grammatical and spelling errors. Comments have been included here with a coding system to preserve anonymity.

13. Exemplified by the movement’s rallying phrase “wwg1wga” or “where we go 1 we go all”. There is speculation this phrase was adopted from either a speech by John F. Kennedy, or was adopted from the movie White squall. See M. Rothschild, 2018. “Q Anon jargon, explained,” Daily Dot (3 July), at, and Internet Movie Database (IMDb), n.d. “Quotes from White squall,” n.d., at



M. AbalakinaPaap, W.G. Stephan, T. Craig, and W.L. Gregory, 1999. “Beliefs in conspiracies,” Political Psychology, volume 20, number 3, pp. 637–647.
doi:, accessed 11 January 2021.

J. Adams and V.J. Roscigno, 2005. “White supremacists, oppositional culture and the World Wide Web,” Social Forces, volume 84, number 2, pp. 759–778.
doi:, accessed 11 January 2021.

T. Aistrope and R. Bleiker, 2018. “Conspiracy and foreign policy,” Security Dialogue, volume 49, number 3, pp. 165–182.
doi:, accessed 11 January 2021.

A. Al-Rawi, J. Groshek, and L. Zhang, 2019. “What the fake? Assessing the extent of networked political spamming and bots in the propagation of #fakenews on Twitter,” Online Information Review, volume 43, number 1, pp. 53–71.
doi:, accessed 11 January 2021.

B. Altemeyer, 2006. “The authoritarians,” at, accessed 11 January 2021.

J.M. Bale, 2007. “Political paranoia v. political realism: on distinguishing between bogus conspiracy theories and genuine conspiratorial politics,” Patterns of Prejudice, volume 41, number 1, pp. 45–60.
doi:, accessed 11 January 2021.

G. Bastin and M. Bouchet-Valat, 2014. “Media corpora, text mining, and the sociological imagination — A free software text mining approach to the framing of Julian Assange by three news agencies using R. TeMiS,” BMS: Bulletin of Sociological Methodology, number 122, pp. 5–25.
doi:, accessed 11 January 2021.

K. Benoit, K. Watanabe, H. Wang, P. Nulty, A. Obeng, S. Müller, and A. Matsuo, 2018. “quanteda: An R package for the quantitative analysis of textual data,” Journal of Open Source Software, volume 3, number 30, 774.
doi:, accessed 11 January 2021.

J.W. Boumans and D. Trilling, 2016. “Taking stock of the toolkit: An overview of relevant automated content analysis approaches and techniques for digital journalism scholars,” Digital Journalism, volume 4, number 1, pp. 8–23.
doi:, accessed 11 January 2021.

B. Carter, 2018. “What is QAnon? The conspiracy theory tiptoeing into Trump world,” NPR (2 August), at, accessed 11 January 2021.

S. Clarke, 2007. “Conspiracy theories and the Internet: Controlled demolition and arrested development,” Episteme, volume 4, number 2, pp. 167–180.
doi:, accessed 11 January 2021.

S. Clarke, 2002. “Conspiracy theories and conspiracy theorizing,” Philosophy of the Social Sciences, volume 32, number 2, pp. 131–150.
doi:, accessed 11 January 2021.

J. Coaston, 2020. “#QAnon, the scarily popular pro-Trump conspiracy theory, explained,” Vox (21 August), at, accessed 11 January 2021.

J. Coaston, 2019. “The Mueller investigation is over. QAnon, the conspiracy theory that grew around it, is not,” Vox (29 March), at, accessed 11 January 2021.

G. Debord, 2002. Comments of the Society of the Spectacle. Translated by M. Imrie. London: Verso.

K.M. Douglas and R.M. Sutton, 2008. “The hidden impact of conspiracy theories: Perceived and actual influence of theories surrounding the death of Princess Diana,” Journal of Social Psychology, volume 148, number 2, pp. 210–222.
doi:, accessed 11 January 2021.

S. Dragoš, 2019. “Factors of radicalization,” Šolsko Polje, volume 29, numbers 5–6, pp. 107–131, at, accessed 11 January 2021.

D.W. Drezner, 2010. “The paranoid style in world politics,” Spectator (London) (8 May), at, accessed 11 January 2021.

U. Eco, 1995. “Ur-fascism,” New York Review of Books (22 June), at, accessed 11 January 2021.

T. Elfrink, 2019. “Trump retweets QAnon conspiracy theorist, via Larry the Cable Guy, to slam the TSA,” Washington Post (20 March), at, accessed 11 January 2021.

M. Fenster, 2008. Conspiracy theories: Secrecy and power in American culture. Revised and updated edition. Minneapolis: University of Minnesota Press.

M. Fluck, 2015. “Theory, ‘truthers’, and transparency: Reflecting on knowledge in the twenty-first century,” Review of International Studies, volume 42, number 1, pp. 48–73.
doi:, accessed 11 January 2021.

T. Goertzel, 1994. “Belief in conspiracy theories,” Political Psychology, volume 15, number 4, pp. 731–742.
doi:, accessed 11 January 2021.

S. Hagen, D. de Zeeuw, S. Peeters, E. Jokubauskaite, Á. Briones, R. Blennerhassett, C. Ferri, F. Woudstra Hablé, E. Blokbergen, B. Haanshuus, M. Poncin, W. Hilhorst, and R. Tsapatsaris, n.d. “Understanding normiefication: A cross-platform analysis of the QAnon conspiracy theory,” at, accessed 11 January 2021.

R. Hofstadter, 1965. “The paranoid style in American politics,” In: R. Hofstader The paranoid style in American politics, and other essays. New York: Knopf, pp. 3–40.

O.R. Holsti, 1969. Content analysis for the social sciences and humanities. Reading, Mass.: Addison-Wesley.

Internet Movie Database (IMDb), n.d. “Quotes from White squall,” at, accessed 11 January 2021.

D. Jolley and K.M. Douglas, 2014. “The effects of anti-vaccine conspiracy theories on vaccination intentions,” PLoS ONE, volume 9, number 2, e89177.
doi:, accessed 11 January 2021.

B.J. Kelley and Hatewatch Staff, 2019. “QAnon conspiracy increasingly popular with antigovernment extremists,” Southern Poverty Law Center (23 April), at, accessed 11 January 2021.

M. Kelly-Hedrick, P.H. Grunberg, F. Brochu, and P. Zelkowitz, 2018. “‘It’s totally okay to be sad, but never lose hope’: Content analysis of infertility-related videos on YouTube in relation to viewer preferences,” Journal of Medical Internet Research, volume 20, number 5, e10199.
doi:, accessed 11 January 2021.

K. Krippendorff, 2004. Content analysis: An introduction to its methodology. Second edition. Thousand Oaks, Calif.: Sage.

D. Kurtzleben, 2017. “Trump embraces one of Russia’s favorite propaganda tactics — Whataboutism,” NPR (17 March), at, accessed 11 January 2021.

E. Laclau, 2005. “Populism: What’s in the name?” In: F. Panizza (editor). Populism and the mirror of democracy. London: Verso, pp. 32–49.

I. Lakatos, 1970. “Falsification and the methodology of scientific research programmes,” In: I. Lakatos and A. Musgrave (editors). Criticism and the growth of knowledge. Cambridge: Cambridge University Press, pp. 91–196.
doi:, accessed 11 January 2021.

P.G. Lange, 2007. “Commenting on comments: Investigating responses to antagonism on YouTube” (31 March), paper presented Society for Applied Anthropology Conference, Tampa, Fla.

M. Laruelle, 2012. “Conspiracy and alternate history in Russia: A nationalist equation for success?” Russian Review, volume 71, number 4, pp. 565–580.
doi:, accessed 11 January 2021.

J. Lehman, 2012. “A brief explanation of the Overton Window,” Mackinac Center for Public Policy, at, accessed 7 July 2012.

P. Leman, 2007. “The lure of the conspiracy theory,” New Scientist (11 July), at, accessed 11 January 2021.

R. Lingam and N. Aripin, 2017. “Comments on fire! Classifying flaming comments on YouTube videos in Malaysia,” Jurnal Komunikasi, Malaysian Journal of Communication volume 33, number 4, pp. 104–118.
doi:, accessed 11 January 2021.

C.D. Manning and H. Schutze, 1999. Foundations of statistical natural language processing. Cambridge, Mass.: MIT Press.

J.W. McHoskey, 1995. “Case closed? On the John F. Kennedy assassination: Biased assimilation of evidence and attitude polarization,” Basic and Applied Social Psychology, volume 17, number 3, pp. 395–409.
doi:, accessed 11 January 2021.

D.T. Miller, 2019. “Topics and emotions in Russian Twitter propaganda,” First Monday, volume 24, number 5, at, accessed 11 January 2021.
doi:, accessed 11 January 2021.

J.M. Miller, K.L. Saunders, and C.E. Farhart, 2016. “Conspiracy endorsement as motivated reasoning: The moderating roles of political knowledge and trust,” American Journal of Political Science, volume 60, number 4, pp. 824–844.
doi:, accessed 11 January 2021.

D. Murthy and S. Sharma, 2019. “Visualizing YouTube’s comment space: Online hostility as a networked phenomena,” New Media & Society, volume 21, number 1, pp. 191–213.
doi:, accessed 11 January 2021.

A. Oksanen, D. Garcia, A. Sirola, M. Näsi, M. Kaakinen, T. Keipi, and P. Räsänen, 2015. “Pro-anorexia and anti-pro-anorexia videos on YouTube: Sentiment analysis of user responses,” Journal of Medical Internet Research, volume 17, number 11, e256.
doi:, accessed 11 January 2021.

P. Reilly, 2014. “The ‘Battle of Stokes Croft’ on YouTube: The development of an ethical stance for the study of online comments,” Sage Research Methods.
doi:, accessed 11 January 2021.

B. Rieder, 2015. “YouTube data tools,” version 1.10, at, accessed 11 January 2021.

M.E. Roberts, B.M. Stewart, D. Tingley, C. Lucas, J. Leder-Luis, S. Kushner Gadarian, B. Albertson, and D.G. Rand, 2014. “Structural topic models for open-ended survey responses,” American Journal of Political Science, volume 58, number 4, pp. 1,064–1,082.
doi:, accessed 11 January 2021.

M. Rothschild, 2018. “Q Anon jargon, explained,” Daily Dot (3 July), at, accessed 11 January 2021.

T. Sanders and H.G. West, 2003. “Power revealed and concealed in the New World Order,” In: H.G. West and T. Sanders (editors). Transparency and conspiracy: Ethnographies of suspicion in the new world order. Durham, N.C.: Duke University Press, pp. 1–37.
doi:, accessed 11 January 2021.

T. Schmiedel, O. Müller, and J. vom Brocke, 2018. “Topic modeling as a strategy of inquiry in organizational research: A tutorial With an application example on organizational culture,” Organizational Research Methods, volume 22, number 4, pp. 941–968.
doi:, accessed 11 January 2021.

J. Sullivan, 2017. “The slippery slope of Trump’s dangerous ‘whataboutism’,” Foreign Policy (7 February), at, accessed 11 January 2021.

V. Swami, R. Coles, S. Stieger, J. Pietschnig, A. Furnham, S. Rehim, and M. Voracek, 2011. “Conspiracist ideation in Britain and Austria: Evidence of a monological belief system and associations between individual psychological differences and realworld and fictitious conspiracy theories,” British Journal of Psychology, volume 102, number 3, pp. 443–463.
doi:, accessed 11 January 2021.

G. Veletsianos, R. Kimmons, R. Larsen, T.A. Dousay, and P.R. Lowenthal, 2018. “Public comment sentiment on educational videos: Understanding the effects of presenter gender, video format, threading, and moderation on YouTube TED talk comments,” PLoS ONE, volume 13, number 6, e0197331.
doi:, accessed 11 January 2021.

K. Welbers, W. Van Atteveldt, and K. Benoit, 2017. “Text analysis in R,” Communication Methods and Measures, volume 11, number 4, pp. 245–265.
doi:, accessed 11 January 2021.

J.A. Whitson and A.D. Galinsky, 2008. “Lacking control increases illusory pattern perception,” Science, volume 322, number 5898 (3 October), pp. 115–117.
doi:, accessed 11 January 2021.

S.C. Woolley and P.N. Howard, 2016. “Political communication, computational propaganda, and autonomous agents — Introduction,” International Journal of Communication, volume 10, pp. 4,882–4,890, and at, accessed 11 April 2019.

I. Yablokov, 2015. “Conspiracy theories as a Russian public diplomacy tool: The case of Russia Today (RT),” Politics, volume 35, numbers 3–4, pp. 301–315.
doi:, accessed 11 January 2021.

D. Zarefsky, 1984. “Conspiracy arguments in the LincolnDouglas debates,” Journal of the American Forensic Association, volume 21, number 2, pp. 63–75.
doi: ttps://, accessed 11 January 2021.




FindTopicsNumber estimate for total topic number
Appendix Figure 1: “FindTopicsNumber” estimate for total topic number.



searchK estimate for total topic number
Appendix Figure 2: “searchK” estimate for total topic number.



FindTopicsNumber topic number estimate for comments with 10+ likes
Appendix Figure 3: “FindTopicsNumber” topic number estimate for comments with 10+ “likes”.



FindTopicsNumber topic number estimate for comments with 70+ likes
Appendix Figure 4: “FindTopicsNumber” topic number estimate for comments with 70+ “likes”.


Appendix topic model label list 1 (full corpus)

Topic 1:
don, way, something, lot, trust, understand, call, channel, support, potus, feel, check, praying, care, seen, either, mind, wow, listen, crazy

Topic 2:
state, deep, someone, media, saying, last, talk, question, evidence, times, comment, etc, ask, lost, people, telling, won, ready, march, opinion

Topic 3:
time, love, really, great, bill, work, keep, hope, never, getting, jordan, videos, smith, wwg1wga, hard, tell, best, stuff, better, job

Topic 4:
god, back, thank, bless, please, name, patriots, book, pray, glad, soon, stay, family, help, wonder, home, bush, safe, red, gone

Topic 5:
good, many, years, day, long, trying, happen, post, information, ago, talking, year, dont, next, enough, end, knows, days, watching, use

Topic 6:
believe, even, yes, big, find, everyone, read, already, put, give, guy, heard,, research, try, start, sorry, reason, looking, follow

Topic 7:
children, old, evil, sick, women, child, woman, sex, age, jews, ginsburg, men, court, man, kids, gay, hate, marriage, ruth, supreme

Topic 8:
look, new, thanks, always, news, anyone, coming, let, plan, bad, info, hear, youtube, around, another, making, exactly, since, posts, qanon

Topic 9:
video, stop, everything, maybe, control, lionel, point, else, israel, part, free, behind, msm, fact, person, dead, proof, movement, run, public

Topic 10:
going, said, president, still, hillary, clinton, obama, remember, justice, happened, china, guys, never, went, cia, office, time, russia, since, arrested

Topic 11:
trump, money, government, results, america, country, american, white, military, house, war, law, vote, family, black, democrats, pay, corrupt, usa, states

Topic 12:
right, real, truth, fake, show, true, jones, says, alex, wrong, stupid, shit, little, wake, left, false, made, following, space, message

Topic 13:
think, nothing, thing, lol, anything, things, ever, done, thought, actually, man, away, mean, today, agree, might, different, assange, full, wait

Topic 14:
people, watch,, world, god, jesus, every, must, evil, life, live, power, problem, human, history, christ, lord, word, cause, bible

Appendix topic model label list 2 (comments with 10+ “likes”)

Topic 1:
people, back, think, hillary, remember, believe, cnn, thought, real, fake, anything, anyone, death, msnbc, tried, really, john, whole, full, drops

Topic 2:
information, children, bohemian, ranch, order, hollywood, grove, pedophiles, society, creek, poindexter, rent, texas, others, cibolo, guests, hubertus, saint, scalia, parties

Topic 3:
time, thing, don, really, big, said, look, please, something, right, jones, think, never, last, long, made, away, enough, everything, ever

Topic 4:
wwg1wga, great, already, msm, getting, plan, light, times, maga, welcome, watching, always, says, actually, war, bad, true, history, deal, conspiracy

Topic 5:
praying, watch, thanks, love, keep, work, pray, potus, post, left, media, today, listen, days, coming, together, soon, speak, awesome, dave

Topic 6:
show, still, live, laws, care, vote, democrats, dead, man, work, trust, satan, party, oyvey, prison, wall, god, home, never, parents

Topic 7:
good, women, man, love, right, hard, hate, jesus, men, lot, book, america, wrong, stand, bad, many, life, angels, mean, father

Topic 8:, results, day, don, must, job, hear, heard, boom, better, never, either, public, controlled, else, correct, feel, end, #wwg1wga, security

Topic 9:
state, nothing, hope, patriots, deep, think, glad, yes, lol, agree, news, someone, white, behind, talk, info, since, joke, wait, said

Topic 10:
everyone, people, red, gay, straight, help, right, anyone, others, around, lives, things, less, opinion, community, especially, brought, children, sex, actually

Topic 11:
evil, old, justice, sick, ginsburg, children, child, court, age, china, supreme, clinton, ruth, woman, looks, jews, years, bader, ginsberg, kids

Topic 12:
trump, god, thank, president, bless, truth, always, many, family, world, craig, video, said, patriot, country, every, ever, patriots, best, brother

Appendix topic model label list 3 (comments with 70+ “likes”)

Topic 1:
good, god, watch, work, thank, country, thanks, hard, praying, hear, craig, late, security, patriot, soon, actually, someone, sick, told, money

Topic 2:
president, trump, china, potus, back, behind, brother, working, left, clinton, hillary, times, truth, long, asking, ago, almost, chinese, gave, hang

Topic 3:
patriots, keep, wwg1wga, ginsberg, saying, trying, court, supreme, disgusting, enough, old, woman, american, children, ruth, since, says, views, done, lie

Topic 4:
evil, love, man, sick, right, age, agree, group, world, believe, don, change, kids, stay, crazy, hate, absolutely, head, stand, parents

Topic 5:
people, dead, state, think, always, democrats, point, good, stop, anyone, controlled, door, israeli, list, media, speak, welfare, still, party, years

Topic 6:
women, ginsburg, mother, nothing, looks, bader, ruth, really, away, witch, great, working, system, communist, child, days, funny, rats, satan, democratic

Topic 7:, bless, bond, results, year, economy, another, sell, end, boom, interest, let, many, dave, everyone, owe, best, bing, check, private

Appendix topic model label list 4 (comments referencing China)

Topic 1:
china, trump, far, left, people, really, world, said, anti, president, system, evil, security, america, made, government, bad, right, american, schools

Topic 2:
chinese, china, hillary, agent, spy, years, clinton, trump, hilary, think, tax, don, believe, trumps, dung, feinstein, computer, pray, hack, world

Topic 3:
china, working, chinese, sick, google, emails, many, cover, information, aluminium, lieu, senator, linked, traitor, email, hrc, everything, system, world, white

Topic 4:
china,, israel, results, america, people, russia, jews, time, nothing, god, country, many, south, black, communication, hillderbeast, run, death, mean

Topic 5:
people, ranch, bohemian, order, creek, poindexter, cibolo, guests, hubertus, rent, saint, keep, china, society, grove, many, trump, believe, news, children

Topic 6:
people, china, trump, remember, many, world, great, america, chinese, country, president, lord, evil, new, right, says, years, look, russia, nations

Topic 7:
china, russia, trump, sold, chinese, clinton, server, yes, hillary, president, back, real, secrets, hrc, military, money, said, asking, access, emails


Editorial history

Received 10 July 2019; revised 10 October 2020; accepted 8 January 2021.

Copyright © 2021, Daniel Taninecz Miller. All Rights Reserved.

Characterizing QAnon: Analysis of YouTube comments presents new conclusions about a popular conservative conspiracy
by Daniel Taninecz Miller.
First Monday, Volume 26, Number 2 - 1 February 2021