Understanding Normiefication

A Cross-Platform Analysis of the QAnon Conspiracy Theory

The results from this project are also uploaded on this webpage.

Team Members

Sal Hagen, Daniel de Zeeuw, Stijn Peeters, Emilija Jokubauskaite, Ángeles Briones, Rachel Blennerhassett, Carmen Ferri, Flora Woudstra Hablé, Esther Blokbergen, Birgitte Haanshuus, Marlou Poncin, Willem Hilhorst, Ryan Tsapatsaris

Visualizations by Ángeles Briones

Contents

Summary of Key Findings

Normiefication is a vernacular concept that describes a process of normalization where “underground” content from fringe subcultural online communities travels to and is popularized on mainstream social media platforms and news media. The concept borrows from subcultural actor language where “the mainstream” is said to be populated by “normies”: regular people that are not familiar with the Internet’s latest subcultural trends. Our research explores the various pathways of normiefication in an empirical manner, inquiring whether such a process can indeed be said to exist, and how exactly it works in a particular case. To this end, it takes the far-right QAnon conspiracy theory as a case study. Does this case warrant the concept of normiefication?

To a large extent, our findings can be said to confirm the “normiefication thesis”. We found that the QAnon conspiracy first appears on the imageboard 4chan (28 October 2017) before migrating to Reddit and 8chan (November 2017), more “mainstream” platforms (YouTube and Facebook), and eventually news media (New York Times, Washington Post, CNN). The results imply that platforms like YouTube and Reddit could operate as “bridges,” forming intermediaries that connect the “deep vernacular” with the “surface” web. Further, the findings suggest a slight “Streisand effect” after mainstream media covered the conspiracy, since it aligns with increased mentions of QAnon on other platforms, thus providing “oxygen” to once-fringe ideas (Phillips 2018). This reverberation occurred on more mainstream platforms like YouTube and Reddit, but also on QAnon’s birthplace, 4chan. As an exception to this finding, QAnon-related activity on 8chan seemed less affected by mainstream media coverage, implying a core group of somewhat isolated yet strongly committed Q-theorists.

1. Introduction

The QAnon conspiracy was born on 28 October 2017 with a 4chan post alleging that a “deep state” is working against Trump and his supporters (Bank, Stack & Victor, 2018). The name of this conspiracy derives from author of the original post, who claimed to be a White House insider with “Q level security clearance”. The actual contents of the deranged conspiracy are not of interest here. Rather, of interest is how it spread across the Internet. While from the outsider’s perspective, it initially seemed like the far-right conspiracy theory lived and died on 4chan, on 31 July 2018, “offline” QAnon supporters suddenly appeared at a Trump rally in Tampa, Florida. Subsequently, news outlets like CNN started reporting on the once-fringe idea. How did such an unexpected diffusion transpire?

Figure 1: The first ‘Q’ post on 4chan/pol/, retrieved from archive.4plebs.org.

This diffusion of subcultural ideas can perhaps be captured with the notion of normiefication. Normiefication has its roots in the actor-language “normie”, a word often used on the imageboards 4chan and 8chan to describe people who are not part of their online subculture and remain within the realms and discourses of the “mainstream” (Nagle, 2017). In light of the growing influence of these sites on various world-historical events like Trump’s election as US president, the purpose of this project is to test and better understand this process as one of normiefication, where content travels across different platforms. This is especially interesting when deeply vernacular concepts and conspiracy theories, which have extremely convoluted explanations and origins, start to appear among people attending Trump rallies.

Figure 2: Initial representation of the different layers from the deep vernacular to the mainstream surface web (De Zeeuw, 2019).

The notion of normiefication reflects an heuristic that conceptualises the lower layers of a “deep vernacular Web” that boil up to and eventually popularise on the mainstream “surface Web” (De Zeeuw and Tuters, 2019 [forthcoming]). We also suggested that some platforms (e.g. Reddit and YouTube) act as intermediaries between the deep and surface layers, exercising a “bridge” function. Since this cultural divide between Internet layers exists in the domain of the imaginary (in the sense that it is not at all technically or institutionally specified, but reflects the way users imagine the space they inhabit), the process of normiefication could perhaps be empirically grounded using digital methods.

The curious fringe-to-mainstream path that the QAnon conspiracy took forms an interesting case study into how a niche concept can move through the different strata of the Web and ends up being reported on by the mainstream media. Tracing such diffusion might shine light on how fringe areas of the Web might form hotbeds for the spread of outlandish ideas and their subsequent normalization. It also shines light on the role of the “mainstream”, which might willingly or unwillingly provide oxygen to fringe ideas. Uncritical reporting on antagonistic web communities, “trolls”, or the so-called “alt-right” has been criticised by Whitney Phillips for unintentionally amplifying the often harmful messages of fringe actors (2018). This has led her and others to call for a more informed mapping of the various collective configurations that exist within these online spaces:

Taking the time to map — to accurately map — the repeated, fractured, reconfiguring mobilizations emerging from anonymous and pseudo-anonymous spaces online allows us to understand where we are and how we got here. [...] fully contextualizing our present moment—particularly given how tenuous facts in our present moment have become—puts us in a better position to safeguard the actual record, and to carefully parse symptom from disease. (Phillips, Coleman & Beyer, 2017)

Instead of focusing on anonymous and pseudonymous spaces (like 4chan and 8chan) as isolated spaces, here we aim to assess the “actual record” of their alleged influence (or a lack thereof) through a comparative cross-platform approach. To do so, we compare QAnon-related data from 4chan, 8chan, Reddit, Youtube, Facebook, and online news media.

Figure 3: An article on QAnon in The Washington Post (Stanley-Becker, 2018).

2. Initial Data Sets

We scrutinised the prevalence of the QAnon conspiracy across six online spheres. Logically, 4chan and 8chan were included in the dataset because they are the platforms on which the nebulous ‘Q’ supposedly posted. Reddit and Youtube were chosen because of their alleged role as bridges for the popularisation of fringe far right ideas and cultural productions like memes (Zannettou et al., 2018; Lewis, 2018). Facebook was chosen as a means to study the conspiracy’s dissemination on a popular social media platform. Lastly, articles on QAnon from online news media were included to study when the conspiracy ultimately boiled up to the “surface”. Because of the limited availability of recent Reddit data, we were obliged to handle October 2018 as the cut-off point in the timeframe, and October 2017 served as a logical starting point.

2.1 4chan

Data was collected from 4chan/pol/ board with the tool 4CAT (Peeters & Hagen, 2018). We merged two datasets. Firstly, we collected “Calm Before the Storm” threads, specific posts that are dedicated to the discussion of QAnon. These were collected within the timeframe of 28 November 2013 (the first appearance) to 8 January 2019 by getting all the threads that had either “cbts” or “calm before the storm” in the title of the first post (the OP). Secondly, we retrieved all posts that mentioned “q” and “qanon” (see appendix I for the specific queries).

2.2. 8chan

8chan data was collected via a collection of posts from “QAnon.news”, a site of unclear origin that collects QAnon-related discussions and information and offers it as packaged archives. Qanon.news collects any QAnon-related discussion, and describes the data as a "complete archive" of Q posts. As historical data from 8chan itself is not readily available, this archive offered a useful alternative. After tinkering with the data, there seemed to be little reason to doubt their veracity and completeness, but follow-up research would need to more thoroughly verify the integrity of these archives.

In total, the archive offered by qanon.news contained 4,563 threads, virtually all from the board /qresearch/ - a board (i.e. subforum) on 8chan dedicated to discussing “research” about QAnon's posts and theories. The data covers the period between November 2017 and November 2018.

The posts contained within the archive came primarily in the form of JSON files of a non-standard format. After inspection of a sample of the data, the relevant data fields were filtered from the full data set and reduced to a spreadsheet containing one record per thread, listing the thread title and metadata (date of posting, amount of replies and the relative size of the thread compared to the longest thread found within the dataset). Additionally, as part of the hyperlink analysis of the full social media platform dataset (see section 5.3) domain names used in the thread's first post were extracted and included separately.

2.3 Reddit

Reddit data was collected through Reddit content hosted on Google BigQuery and collected by Pushshift (Baumgartner, 2018). Firstly, all subreddits were queried for mentions of “qanon” and “q” from October 2017 until October 2018 (see appendix I for the exact queries), treating this as the main data for analysis. Some data was found to be missing from the dataset, since Pushshift data is only collected at the end of every month, while some subreddits (e.g. r/cbts_stream or r/thegreatawakening) were terminated (“banned”) before the end of the month (respectively, March and September in our case).

The initial dataset was narrowed down in two ways. The top 20 overall subreddits with the highest frequencies of the terms of “qanon” and “q” were used for the analysis of the change of the use of these terms over time (presented in section 4.2), focusing on the data of subreddits that were generally the most engaged in the discussion. A different approach was taken to extract the most relative subreddits for each month: for each month of the 13-month-period the top 20 subreddits were found that mention “qanon” or “q” most frequently. From each of them, posts that contain the terms were extracted (17933 posts in total).

2.4 YouTube

Youtube data was collected through three different steps. Firstly, we qualitatively compiled a list of channels dedicated to QAnon-related discussions by simply searching for “qanon” and exploring the channels of recommended videos. Next, we retrieved the YouTube domains from high scoring Reddit post related to QAnon from r/CBTS, r/the_great_awakening and r/The_Donald. This resulted in a curated list of QAnon Youtubers. This resulted in the following channels:

• Lionel Nation (~202,000 subscribers)
• Destroying the Illusion (~136,000 subscribers)
• JustInformed Talk (~108,000 subscribers)
• Prayingmedic (~107,000 subscribers)
• TracyBeanz (~106,000 subscribers)
• SphereBeing Alliance (~94,000 subscribers)
• Lift The Veil (~53,000 subscribers)
• Bill Smith (~45,000 subscribers)

The video data from Youtube channels on the curated list was downloaded and proceeded to download the data of these channels. Secondly, we queried a dataset of thousands of videos by far-right Youtube channels compiled by an outside expert on whether they mentioned “q” or “qanon” in the title or description (see queries in appendix I). Thirdly, we collected video data from the first 500 results when searching for “qanon” using the YouTube Data Tools (Rieder, 2015). After merging these three datasets, we deleted false positives and duplicate videos manually.

2.5 Facebook

The initial dataset for Facebook was collected using the tool netvizz (Rieder, 2013). Due to known issues with large-scale data collection on this platform (Rieder, 2018), we were only able to query a limited number of public pages. These were identified by searching with the terms ‘qanon’, ‘qarmy’, and ‘wwg1wga’ (“where we go one we go all,” a popular slogan associated with QAnon). Pages with more than 1000 likes were selected for the dataset. These include pages like “QAnon Curator”, “QAnon Army”, and “QAnon France”. This only provided a limited view on Q-related activity on Zuckerberg’s platform, but we decided to include it nonetheless as it could provide an at least exploratory view on the prevalence of the conspiracy on Facebook.

2.6 Online News Media

Finally, we collected articles on the QAnon conspiracy by online news media. We used three different methods to do so in order to make the dataset as comprehensive as possible. Firstly, the LexisNexis Academic newspaper archive was queried for all English articles related to the search term “QAnon”. The LexisNexis results were subsequently compiled in Google Sheets, and we removed some duplicates from the resulting list of about 700 articles. The list was also further filtered by deleting articles that referred to “QAnon” as an Armenian musical instrument, and a few other irrelevant results. Secondly, Google News was queried for articles relating to QAnon to enrich the LexisNexis results. Thirdly, we added articles from news sources that were frequently mentioned on Reddit in relation to the far-right conspiracy. To do so, we extracted the top fifty domain names that had been mentioned in posts mentioning ‘Q’ or ‘QAnon’ from r/news r/politics, and r/worldnews. We chose these subreddits as they are fairly popular and would thus likely lead to provide ‘mainstream’ sources, instead of the fringe ones found on e.g. r/thegreatawakening. From the popular domains, we filtered out non-news websites (like YouTube). Then, we used Google and its “site:” operator with “qanon” (e.g. “site:vox.com qanon”) to retrieve articles from these websites on the topics. Relevant articles on the first page of the Google search results page that were not yet in the dataset were added. These three steps resulted in a total of 383 articles, from sources ranging from Quartz to The Washington Post.

3. Research Questions

• Can the concept of normiefication be empirically traced?
• When and how did QAnon “normiefy” and move from its subcultural origins to mainstream strata of the Web?

4. Methodology

4.1 Merging and Visualizing the Data

We merged all the datasets as defined in section 2 in one large datasheet. Since the objective was to trace the prevalence of the QAnon conspiracy, we had to determine what counted as a “frequency unit” with which we could measure this prevalence. We did so for each platform. While this would allow to map the frequencies of the Q-related units, we also wanted to determine how much these units were engaged with across platforms. As such, we also determined an “engagement unit”. The engagement units per platform were translated to a score between 1 and 100 so we could plot the cross-platform data on the same panes.

The frequency units and engagement units we ultimately settled on are as follows:

• 4chan
  • Frequency unit: The first post of a thread (the OP) on 4chan/pol/ containing “qanon” or “q” in the post title or body (see appendix I for the exact query) or the first post of a /cbts/ “general” thread.
  • Engagement unit: The amount of replies in the thread (thread length).
• 8chan
  • Frequency unit: The first post of a thread (the OP) on 8chan/qresearch/ containing “qanon” or “q” in the post subject or body (see appendix I for the exact query).
  • Engagement unit: The amount of replies in the thread (thread length).
• Reddit
  • Frequency unit: A post on the top 20 subreddits per each month that mention “qanon” or “q” most frequently (see appendix I for the exact query).
  • Engagement unit: The score of the post using Reddit’s voting mechanism (i.e. upvotes - downvotes).
• YouTube
  • Frequency unit: A single video in our merged YouTube dataset.
  • Engagement unit: The amount of comments on the video.
• Facebook
  • Frequency unit: A post on the selected Facebook groups and pages.
  • Engagement unit: The amount of comments on the post.
• Online news media
  • Frequency unit: A news article.
  • Engagement unit: The CrowdTangle score of the article. This is a metric based on the amount of engagements of the article on other websites like Twitter, Facebook, and Reddit.

Using this data, two graphs were created with RAWGraphs and Adobe Illustrator. Firstly, we used the frequency units and created histograms per platform, where each bar represented one day. These histograms were then merged on one pane for comparison. Secondly, we generated scatter plots per platform, where each dot represented one frequency unit, the x-axis represented the date, and the y-axis represented the corresponding engagement unit. We then added a “contour plot” on top of these scatterplots to highlight the concentration of and engagement with the frequency units over time. For both graphs, we used the timeframe of October 2017 until October 2018.

4.2 Additional Analyses

Supplementary to the main analysis, some additional analyses were conducted, touching upon the contents of the data. Firstly, in order to map out the issue spaces of the conspiracy on Reddit we visualised which subreddits mentioned “Q” and “QAnon” over time. The dataset of all Reddit posts in the 13-month-period containing these terms (presented in section 2.3) was grouped per subreddit. A streamgraph was made with RAWgraphs to show the pervasiveness of the conspiracy across subreddits over time.

Next, the change between the prevalence of terms “Q” and “QAnon” on Reddit over time was analysed. It was done because the latter nomenclature arguably marks a point of crystallization since it only appeared when the conspiracy had been around for a few months. The frequencies of mentions for “q” and “qanon” in the top 20 subreddits most engaged with the topic were calculated separately. A bumpchart was then made (using RAWgraphs) showing the moment of “QAnon” overtaking “Q”, which can be referred to as the crystallization of the term.

Lastly, to gain insight into what information sources were linked to most often in the given issue space, we extracted hyperlink networks from the merged datasets. For each post, the linked domain names (e.g. digitalmethods.net) were extracted from the post’s text content. These links were then mapped as a Gephi network, consisting of a set of “seed” nodes (the social media platforms) and nodes representing the links themselves. Weighted edges between seed nodes and link nodes represented the prominence of the given domain names on the respective platforms. The link network graph thus represents (1) on which social media platforms a given site was linked to and (2) how often it was linked to per platform. This data could then be used to get an impression of information source popularity per site (see section 5.3)

5. Findings

5.1 General Findings

Figure 4: The prevalence of the QAnon-conspiracy across 4chan, 8chan, Reddit, YouTube, Facebook, and online news media from 28 October 2017 to October 2018.

Although complicated by limited data access, our research suggests that the QAnon conspiracy indeed diffused through a process similar to what we conceptualise as normiefication. It originated on 4chan, after which it quickly found a public of devotees on Reddit, 8chan, and YouTube. After “leaving” 4chan, the conspiracy was relatively consistently discussed on the latter three platforms, although various Q-related subreddits were banned, limiting the prevalence of the conspiracy theory on Reddit. Interestingly, it was only until February 2018 that the Q-related discussion on 8chan started to become common.

Nine months after its inception, online news media started to widely cover the conspiracy. Notably, this sparked some Q-related discussion on 4chan again, even though it had been absent for a while. This implies the online news media indeed provided “oxygen” to the prevalence of such conspiracies, as we will further discuss below.

Figure 5: The prevalence and engagement with the QAnon conspiracy from 28 October 2017 to October 2018 across 4chan, 8chan, Reddit, YouTube, Facebook, and online news media. Green bar denotes the start of media attention.

5.2 Findings Per Platform

To list the findings more in-depth, this section briefly covers the findings per platform.

5.2.1 4chan

Figure 6: Thread frequency and engagement (thread length) of QAnon threads on 4chan/pol/ from October 2017 to October 2018.

QAnon began on the 4chan/pol/ board in October 2017 and there are two concurrent peaks of QAnon posts on the platform from the beginning of October to the end of November. QAnon activity on 4chan drops off sharply for both peaks at the end of November 2017. This corresponds with a post from Q on the CBTS thread announcing that 4chan as a platform had been “compromised” and that Q was moving to 8chan - as is reflected in our visualisations. There was a small bump in activity on 4chan in August 2018, which corresponds the media coverage of the conspiracy. Overall, the engagement (i.e. thread length) is fairly varied, but the dedication was especially high when the CBTS threads were still prevalent in the early phases. This suggest conversation after Q’s “compromise” became more casual, in contrast to the intense “research” and speculation before.

5.2.2 8chan

Figure 7: Thread frequency and engagement (thread length) of QAnon threads on 8chan/qresearch/ from October 2017 to October 2018.

On 8chan/pol/, there is a clear increase in posts relating to QAnon in December 2017, which corresponds with the announcement on 4chan that Q was “moving” to 8chan. The /qresearch/ board then quickly becomes consistently active from January 2018 onwards. The most engaged with threads in the data set are again so-called “general” threads, specifically intended for Q-related discussion. As indicated in the graph below, there is an assortment of less popular threads dedicated to discussing specific theories or bits of information as well. However, virtually all threads in the data set over the last two thirds of the 8chan data reach ~750 posts (91% of all threads); the limit after which 8can threads are archived or deleted and comments are disabled. This further confirms that activity remains consistent after Q-related discussion moves from 4chan to 8chan, easily filling up thread after thread. Interestingly, 8chan activity is far more consistently “dedicated” compared to the 4chan activity, where engagement fluctuates more.

Noteworthy is that in contrast with some of the other investigated platforms, there are no clear peaks in activity. Activity plateaus at its peak around July-August 2018, which corresponds with increased mainstream media coverage of QAnon. While this indicates that outside coverage does have some impact on the volume of 8chan-based discussion, given the consistently high activity before this happened the bulk of posts can perhaps be attributed to a “hard core” of posters that have been active on the platform since 4chan passed its baton.

5.2.3 Reddit

Figure 8: Post frequency and engagement (score) of QAnon related posts on Reddit from October 2017 to October 2018.

On Reddit, the first mentions of QAnon appear already on the 28th of October, 2017 the subreddits of r/4chan4trump and r/TranscribersOfReddit. This happens on the same day that the first Q post was made on 4chan/pol. In the few upcoming days it appears and grows on larger subreddits such as r/the_donald and r/conspiracy. Consistent Q specific activity then ensued on the subreddits r/cbts_stream (early 2018) and r/greatawakening (mid-2018). The former subreddit was banned in March 2018 and the latter was banned on September 27th 2018. The frequency of QAnon related posts dramatically increases following Trump’s Rally in Tampa, Florida on 1 August 2018. Around this time, links to Q-related news coverage on r/news and r/politics also spiked. The most upvoted Reddit post in the sample was titled “QAnon Fan Arrested for Threatening Massacre at YouTube Headquarters”, which featured a news report. Because of outliers like these, the scatterplot in fig. 8 appears condensed.

A process of normiefication can arguably also be observed within Reddit. While the conspiracy was first mainly mentioned in more niche subreddits, like r/cbts_stream and r/thegreatawakening, larger and more popular subreddits like r/politics only jumped on the bandwagon in August 2018, at the same time when media sources started reporting on the topic (fig. 9). The disappearance of the niche is of course stimulated by the bans of the Q-specific subreddits.

Figure 9: the growth of the terms “q”or “qanon” in comments on different subreddits for the time period of October 2017 until September 2018. Yellow marks subreddits important for the build-up of the conspiracy, red marks terminated (“banned”) subreddits.

Interestingly, August 2018 was again cemented as a tipping point since from this month onwards, ‘QAnon’ was used more than ‘Q’ in reference to the conspiracy. Indeed, this succession occurs at the same point in which QAnon is receiving coverage from mainstream media outlets.

Figure 10: Frequency of the terms “q”, “qanon”, and “q anon” in comments across Reddit from October 2017- October 2018.

5.2.4 YouTube

Figure 11: Video frequency and engagement (comments) relating to QAnon on YouTube from October 2017 to October 2018.

The first YouTube video on the subject of QAnon was uploaded on November 2nd 2017. Three subsequent peaks in the frequency of videos posted can be seen in February 2018, May 2018, and August 2018. CNN’s report on QAnon in August of 2018 was the most commented on video in the sample, with around 14,000 comments, even though the sample principally included videos from native Youtube creators than those of mainstream media outlets. Again, these highly engaged with videos were real standouts, showing the video platform houses both dedicated channels and ‘viral’ instances related to the conspiracy. This is further emphasised because Q-related videos on the platform were frequent after and before the mainstream attention in August 2018, showing that YouTube is not wholly “mainstream”, despite being the second-most visited site worldwide.

5.2.5 Facebook

Figure 12: Post frequency and engagement relating to QAnon on Facebook from October 2017 to October 2018.

Keeping in mind the much more limited dataset used for Facebook, there were still indications that the number of pages and posts dedicated to the topic of QAnon increased. This increase starting approximately in July 2018, reaching a consistently high level of posts for August and September. As such, activity on these dedicated Facebook pages followed the growth trends of other platforms, and a similar spike in interest following mainstream media coverage.

As a side note, it was interesting to note that several of these pages were dedicated to selling t-shirts with QAnon-related slogans and “artwork” of the kind worn by the rally participants spotted in the news, pointing to another possible type of “bridge-forming” on mainstream social media.

5.2.6 Online News Media

Figure 13: Article frequency and engagement (CrowdTangle score) of QAnon-related articles on online news media from October 2017 to October 2018.

Under the title ‘The Storm Is the New Pizzagate — Only Worse”, the QAnon conspiracy was first covered by New York Magazine on 19 December 2017, referencing “The Storm”, another name for the conspiracy. It took several months before the phenomenon gained widespread attention on this “layer”, however. The majority of the stories on QAnon were published between late July and early September 2018. This correlates with the highest period of Google search results for the term QAnon.

Four major events were identified to drive the QAnon narrative in online news media

1. In late March 2018, actress Roseanne Barr expressed her support for QAnon on Twitter.
2. On 31 July 2018, QAnon supporters was present at a Trump rally in Tampa, Florida.
3. In September 2018, the media wrote about a meeting between Trump and Michael William Lebron, radio personality and a leading QAnon supporter, in the White House.
4. Finally, in October 2018 the perpetrators of two domestic terrorists attacks in the United States were linked to QAnon by the media: the Pittsburgh synagogue shooter and the serial mail bomber who sent pipe bombs to several prominent Democrats, including the Clintons, as well as billionaire and philantropist George Soros.

Figure 14: Annotated line graph of number of QAnon-related articles published on online news media

5.3 Cross-Platform Hyperlink Analysis

We extracted all links contained within the data collected from Facebook, YouTube, Reddit, 4chan and 8chan - i.e. all social media platforms, but not the mainstream media content that was analysed. A visualisation of this directed network graph provides further insight into the types information sources used within the QAnon issue space.

Figure 15: Top domains linked to in the social media data set. Nodes closer to the center are linked to on more social media platforms; nodes nearer the sides of the graph are linked to by one or a small number of platforms. Larger nodes are linked to more often.

Node clusters are clearly visible in a visualisation of this network; each platform has a set of sites that are only linked on that particular platform, which co-exists with a set of sites that are linked to by all platforms (the cluster in the middle). Perhaps most interestingly, clusters of sites appear that are often linked to by some of the social media platforms, but not by others. These clusters suggest some of the platforms we included are similar in the kind of content they link to than others. For instance, the site “kek.gg” - a free image host named after one of 4chan's cult symbols - is located in the corner of 4chan, 8chan and reddit, next to nymag.com, the US magazine that first brought QAnon to mainstream attention. Conversely, a mainstream site like nytimes.com is located squarely in the middle, indicating no preference for a particular platform and emphasizing its status as an information source used by all.

Figure 16: Detail of Figure 15. Highlighted are two nodes that are linked to most prominently on Reddit, 4chan and 8chan; kek.gg and nymag.com. Nytimes.com is highlighted for comparison, being a site linked to by all platforms and therefore being positioned close to the middle of the graph.

One limiting factor here is that a significant percentage of the links found in this data were shortened links (like bit.ly, often used for convenience) or archive links (links to archived versions of the original page). We did not attempt to 'expand' these links and trace them to the original links, which could be an interesting next step.

6. Discussion

What does our limited QAnon case study say about the concept of normiefication? For one, there indeed seems to be a observable “wave” between the “layers”. The conspiracy was most consistently discussed on 4chan and Reddit, before moving to 8chan, YouTube, Facebook, and, eventually, showing its face in reports by news media. 4chan, labelled as the “birthplace of memes” here emphasises this characterisation, being the initial fertile grounds for the “bullshit accumulation” (Tuters et al., 2018) of Q. Reddit might share itself amongst 4chan in this regard, as redditors were quick to pick up on the conspiracy. However, the findings also show limits to equating these lower “strata” of the cultural Web stack, as e.g. 8chan latched on later than 4chan, and the former shows remarkably continuous activity compared to the latter, remaining relatively unaffected by the mainstream coverage.

The findings show news media amplified the QAnon conspiracy. News media coverage alings with increased activity on both 4chan, Reddit, YouTube, and Facebook. However, the negative effects of this amplification remain implicit. It is reasonable to assume that much of the Q-related activity following the news media attention was not as much concerned with the truth value of the conspiracy, but rather elicited ridicule or merely commented on the media storm. Further, while Q-related activity on 4chan spiked shortly after the reports in August 2018, it quickly faded as well, implying the media reports did not provide the conspiracy any substantial legs. However, perhaps these dangers of amplification are more serious on other “layers” like YouTube and Facebook. Follow-up research should delineate and characterise these influences, or the lack thereof.

One unanswered question is where and when the Trump-supporting Q-enthusiasts at the Tampa rally -- who would be characterised as normies by self-styled Internet natives -- came to be engaged with the conspiracy. From our limited findings, it is not clear which point exactly the conspiracy moved from the online to the offline. Such spillovers are not of main concern for a digital methods approach, which attempts to ground their findings in the online (Rogers, 2013). Still, it would nonetheless be informative in relation to the concept of normiefication, as it could pinpoint where obscure, slightly ironic online phenomena like the Q-craze are likely to crystallize into forms of traditional activism.

These differences in engagement with the QAnon conspiracy are already implicit in the limited content analyses we performed. The dominant nomenclature of the conspiracy changed from “Q” to “QAnon” on Reddit after August 2018. While the conspiracy was prevalent throughout the analysed “layers”, the sources used alongside this discussion clearly differ from platform to platform, as became apparent with the hyperlinks analyses. This thus suggest that within the wider QAnon issue public there exist distinct subgroups with their own preferred information sources. The diffusion of the conspiracy should perhaps thus not be understood as a simple expansion of actors concerned with the issue, eventually also incorporating “normies”, but rather points to the establishment of new, related, but distinct issue publics that discuss a shared issue, but are distinct in their use of information sources.

6.1 Limitations

The main limitations of this project arose from equating data across multiple platforms. Can you reasonably compare activity on 4chan/pol/ to 8chan/qresearch/? And do videos on YouTube reasonably equate as ‘frequency units’ to Reddit posts? How do comments on Facebook compare to CrowdTangle engagements with news articles? These are unpreventable limitations when performing cross-platform analyses, as one necessarily has to deal with comparing different platform ontologies. Follow-up research could rethink the steps we took for this project and perhaps generate some more advanced and more comparable engagement metrics.

Further, each platform presented their own limitations in terms of data collections. Our 4chan sample is quite complete, but the 8chan sample only included the board /qresearch/. Since 8chan allows user-generated boards, other relevant boards should perhaps have been included as well, like 8chan/pol/. On Reddit, the QAnon-devoted subreddits r/cbts_stream and r/thegreatawakening were both banned and removed from the website. Because of a slight delay in archiving, data for these subreddits ended earlier than their actual disappearance. Our YouTube sample does not cover all videos on Q, but rather had to rely on a variety of approaches to garner a representative dataset. For Facebook, we only included a relatively small sample of public pages as the platform is increasingly being closed off for research. Similarly, the articles from online news media articles are only a limited sample, and could be expanded to include several of the biggest media outlets. Other platforms that might have been relevant, like Twitter, were also not included in the current research, both because of limited data access and time constraints.

7. Conclusions

This research took the imaginary vernacular concept of the “normie” and attempted to test whether it could be what we refer to as normiefication. Although studying such information diffusion is nothing, this concept highlights the online spread of subcultural ideas and obscure vernacular from obscure origins to mainstream attention, afforded by the ease of shareability of the Internet. Tracing such diffusion might shine light on how fringe areas of the Web might form hotbeds for the spread of outlandish ideas and their subsequent normalization. It also shines light on the role of the “mainstream”, which might willingly or unwillingly provide oxygen to fringe ideas.

As a case study, we traced the QAnon conspiracy across subcultural strata to mainstream layers. To a large extent, our findings can be said to confirm the “normiefication thesis”. We indeed observed a gradual spillover 4chan, Reddit, 8chan, YouTube, Facebook, and, ultimately, online news media. While activity on the origin, 4chan, quickly dwindled, the results suggest platforms like YouTube might function as “bridge platforms” that bring the conspiracy to a wider audience online. The research further suggests online news sources reporting on QAnon in August 2018 did somewhat amplify the conspiracy across platforms, creating a “Streisand effect” and providing “oxygen” to once-fringe ideas (Phillips, 2018). However, the effects of this amplification have to be further explored by analysing how the conspiracy was discussed.

As mentioned, this study merely provided some quantitative insights into the prevalence of the QAnon. Analysis on how the conspiracy was engaged with over time and across platforms would be an informative next step. How did the Q-related discussion change over time and across platforms? Could this identify publics that are engaging with the conspiracy as outright activism, or are there also elements of ironic roleplay to be distinguished? Regarding the concept of normiefication, conducting other case studies could further test the salience of the concept, for instance by tracing the use of a specific meme across subcultural and mainstream Internet platforms.

8. References

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Barkun, Michael (2013). A Culture of Conspiracy: Apocalyptic Visions in Contemporary America. Berkeley, CA: University of California Press

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Milner, Ryan. FCJ-156 Hacking the Social: Internet Memes, Identity Antagonism, and the Logic of Lulz. (2013). The Fibreculture Journal, (Issue 22 2013: Trolls and The Negative Space of the Internet). Retrieved from http://twentytwo.fibreculturejournal.org/fcj-156-hacking-the-social-internet-memes-identity-antagonism-and-the-logic-of-lulz/

Nagle, A. (2017). Kill All Normies: Online Culture Wars from 4chan to Tumblr to Trump and the Alt-Right. London: Zero Books.

Peeters, S. & Hagen, S. (2018). 4CAT: Capturing and Analysis Toolkit (version 1.0).

Phillips, W. (2015). "Chapter 1: Defining Terms: The Origins and Evolution of Subcultural Trolling” in This Is Why We Can't Have Nice Things: Mapping the Relationship Between Online Trolling and Mainstream Culture. Cambridge MA: MIT Press.

Phillips, W. (2017). The Oxygen of Amplification. Retrieved from https://datasociety.net/output/oxygen-of-amplification/

Phillips, W., Coleman, G., & Beyer, J. (2017). Trolling Scholars Debunk the Idea That the Alt-Right’s Shitposters Have Magic Powers. Retrieved from https://motherboard.vice.com/en_us/article/z4k549/trolling-scholars-debunk-the-idea-that-the-alt-rights-trolls-have-magic-powers

Rieder, B. (2013). Studying Facebook via Data Extraction: The Netvizz Application. In Proceedings of the 5th Annual ACM Web Science Conference (pp. 346–355). New York, NY, USA: ACM. https://doi.org/10.1145/2464464.2464475

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Rieder, B. (2018). Facebook’s app review and how independent research just got a lot harder. Retrieved 29 January 2019 from
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Stanley-Becker, I. (2018). ‘We are Q’: A deranged conspiracy cult leaps from the Internet to the crowd at Trump’s ‘MAGA’ tour. The Washington Post. Retrieved from https://www.washingtonpost.com/news/morning-mix/wp/2018/08/01/we-are-q-a-deranged-conspiracy-cult-leaps-from-the-internet-to-the-crowd-at-trumps-maga-tour/?noredirect=on&utm_term=.99a7601295e4

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8. Appendix

Appendix 1: Queries for “Q”

SQL Query used to get mentions of ‘Q’ on the analysed platforms.

WHERE (lower(title) LIKE '% q %'
OR lower(title) LIKE '% q,%'
OR lower(title) LIKE '% q.%'
OR lower(title) LIKE '% q!%'
OR lower(title) LIKE '% q?%'
OR lower(title) LIKE '% q,%'
OR lower(title) LIKE '% q\n%'
OR lower(title) LIKE '% q'
OR lower(title) LIKE '%qanon%'
OR lower(title) LIKE '%q anon%')
AND lower(title) NOT LIKE '%q and a %'