- 18 Jul 2017
Alt-Right Open Intelligence Initiative
Mapping the Alt-Right: The US Alternative Right across the Atlantic
Summary of Key Findings
On Facebook, the alt-right core’s most engaged with content is more extremist, the alt lite’s anti-establishment and the alt-right UK/EU counter-jihadist, thus suggesting a new (and significant) theme to the Alt Right spectrum. The inter-liked page networks for each of the subgroups reveals an insular alt-right core, an alt-lite revolving around Alex Jones, and an UK/EU networked centered around Arktos, with Tommy Robinson isolated. On Twitter the Alt-Right core has ‘significant others’, or those mentioned by 7 or 8 of the core, as indicated by a ‘belonging’ metric; their newly discovered audience, however, is relatively small, as the majority of those they mention are themselves. The alt-right has particular information campaigning styles, including the pairing of hashtags (to link a less extreme issue to one that is more extreme) as well as a particular strategy of event ‘use’, such as in the case of the Berkeley riots over free speech. On YouTube
we found emerging ‘alt-right struggles’ where there is disunity as evidenced by the lack of shared channel subscriptions and featured content as well as a great dislike for many of their videos, showing forms of contestation to their otherwise successful online activism.
This project’s aim is to produce open-source intelligence into the alt-right -- the latter described as "amalgam of conspiracy theorists, techno-libertarians, white nationalists, men’s rights advocates, trolls, anti-feminists, anti-immigration activists, and bored young people" (Marwick & Lewis, 2017).
The project thus focused on mapping the alt-right’s online presence and accounting for some of their key strategies. The hope then was that studying the Internet and social media data could lead to insights about the alt-right as ‘influencers’ as well as concerning the story of their rise in the UK and Europe. It was thus the overall aim of this project to operationalise or set the terms in which influence could be defined, measured and accounted for. Analytically speaking, then, we sought to study the alt-right’s influence: in terms of actors most influential “within” a cluster; in terms of relations “across” clusters; and in terms of distinctive audiences “beyond” clusters.
Regarding the latter, one may also compare each of these followings, thereby gaining a sense of reach in comparison to the other’s. One also could consider these measures overtime. Thus the baselines against which to measure influence would be against one another as well as longitudinally. Do they mingle? Is each of the rise? Whilst this ‘stylised’ methodology is not strictly followed, in the course of the work we return to these individual questions as well as to the overall question of influence.
2. Initial Data Sets
This list consisted of three different sets of actors: (1) the alt-right core, which is being defined as a particular brand of ‘young and educated’ white nationalism and white supremacism, “deeply entwined with social media and staples of internet culture” (Marwick & Lewis ‘17); (2) the so-called alt-right lite, or alt-lite for short, referring to a less extreme faction within the broader far-right ideology of the alt-right, also online; and (3) the alt-right in the UK with links to continental Europe. Here the links to the alt-right may be literal (as one Scandinavian on the list writes for altright.com, based in the U.S.) or more contiguous with the rise of the ‘new right’, with certain similarities in orientation, style and online presence.
In order to map the three alt-right groupings online, we first sourced their websites, Twitter handles, Facebook pages and other online presences such as YouTube
channels and podcast services. It should be noted that a few of these accounts already had been removed by Twitter, especially owing to their extreme content. These removals are part of a cat-and-mouse game, whereby a few of the figures in question have returned under different account names; these reborn Twitter accounts for such significant actors as the Daily Stormer have much lower follower counts than previously, however, perhaps suggesting a different individual or group behind the account or its incipient nature. Where that is the case, we chose not to include the newer account, rather keeping the analysis to the known players of some import. Account removals, however, affect the analysis, for key players are thus missing in the space. The cat-and-mouse game also affects any longitudinal analysis, for an account removal could account for a drop in ‘influence’ in any of the permutations discussed above.
3. Research Questions
We pursued the following research question in consulation with an expert body on the subject:
What is the ‘influence’ of the alt-right (and its online activism), especially in the UK?
When dealing with this central question, related questions emerge:
- To what extent can we recognise the alt-right to be coherent with definable features? Here we map their shared connections Twitter and Facebook. We also map on YouTube their shared subscriptions and featured content.
- What different narratives and topics can be identified among the figures analysed? Are there differences between and within the three sets of the alt-right core, the alt-light, and the alt-right in the EU/UK? Here we map their shared content and themes on Facebook and Twitter.
More specifically, the research projects are as follows:
- Facebook most engaged with content - Core, Alt-lite, UK/EU. Does the same content animate the three subgroups? Are there themes (that animate) ‘missing’ in the Alt Right spectrum?
- Facebook inter-liked page network analysis - Core, Alt-lite, UK/EU
YouTube analysis: Alt-right struggles
- The Alt-right core’s significant others. Who do the alt-right @mention?
- The Alt-right core’s audience. Who @mentions the Alt Right? Does the Alt Right have an audience beyond itself?
- The Alt-right’s significant others according to @mentions (core, alt-lite as well as UK/EU).
- Twitter Hashtag Analysis. Alt-right hashtag information campaigning strategies
- Alt-right subscriber and featured networks. Disunity among the alt-right.
- Disliked video analysis. What is there to dislike about the alt-right?
Facebook page-like network:
What do the facebook-like networks reveal about the connections / network of public figures associated with the alt-right?
How do they relate to figures in UK/EU?
Facebook pages most engaged with content:
What content on the Facebook pages analysed is most popular?
Is the Alt Right engaged by primarily extreme content? How to characterise the most engaged with narratives across the Alt Right, Alt light and Alt UK Europe?
Twitter @mention network:
What do the twitter mentions reveal about the connections / network (significant others) of public figures associated with the alt-right?
How do they relate to figures in UK/EU?
Twitter hashtag analysis:
What hashtags can be identified to unite and divide the three sets of our seed list (core / light / EU&UK)?
Close-reading of shared events/topics, as revealed by the mapping of hashtags.
Channel subscription and featured content networks. To what extent do they subscribe and feature each other’s videos?
Disliked video analysis. Which kinds of videos tend to be (predominantly and greatly) disliked?
Alt-right, alt-lite and alt-right UK/EU’s most engaged with content on Facebook
Alt Right is newsy, Alt light and Alt UK Europe are much webbier with memes (and occasionally youtube videos) most engaged with. For Alt Right, Alt-Right.com is top provider, for Alt light, Milo is top, and for Alt UK EU Infowars has the most engaged with content.
The Alt Right’s most engaged with content is white nationalist as well as anti-establishment. The Alt light is primarily anti-establishment and anti-political correctness. The Alt UK EU is primarily anti-establishment and counter-jihadist.
Here we note the importance of highlighting counter-jihadism as a specific theme, and perhaps part of the Alt Right spectrum, for it animates portions of the UK/EU alt-right specifically.
Figure 1. Treemap displaying most engaged with content of Facebook pages associated with the alt-right core; dark blue being the highest engagement. The circles in the top right represent the engagement relative to the other two sets.
Figure 2. Treemap displaying most engaged with content of Facebook pages associated with the alt-light; dark blue being the highest engagement. The circles in the top right represent the engagement relative to the other two sets.
Figure 3. Treemap displaying most engaged with content of Facebook pages associated with the alt-right in the EU/UK; dark blue being the highest engagement. The circles in the top right represent the engagement relative to the other two sets.
To what extent does the core alt-right network produce the content that is most engaged with across the alt-right and alt-light? Are there distinctive content producers?
Based, then, on a analysis of the similarity/difference of specific, most-engaged-with content across subgroups (core, alt-lite, UK/EU), we see that content does not really travel between the clusters; alt-light content, for example, is not highly engaged with on core pages of the alt-right.
Facebook inter-liked page network
Figure 4. Graph displaying the network of pages liked by the pages associated with the alt-right core connected through the likes between them.
The first thing that immediately becomes clear from this network, is that it is small and enclosed, suggesting that the Facebook activity for the alt-right core is predominantly introvert and, conceivably, mostly concerned with broadcasting. Secondly, there are three new names that this network suggests to add to the name list of the alt-right core: Arktos; Gornahoor; and Jack Donovan.
Figure 5. Graph displaying the network of pages liked by the pages associated with the alt-light connected through the likes between them. http://bit.ly/2udNmnJ
What stands out in this network is that Alex Jones, and associated nodes (like The Obama Deception and Fall of the Republic; both documentaries by Jones) are by far linked to the most. Arktos is largely absent here, and Donald Trump seems to be a relatively marginal node. When looking closer at the different clusters, we could categorize them as follows: green and purple is largely centred around conspiracists; orange and purple is US libertarianism; and blue is established populism.
Figure 6a. Graph displaying the network of Facebook pages liked by the pages associated with the alt-right in the EU/UK connected through the likes between them.
One of the things that is striking about the EU/UK network is how disconnected some of the nodes are, namely the US alt-light clustered around Alex Jones, but also, interestingly Red Ice as well as Tommy Robison (while Jones is connected to his own cluster, Red Ice as well as Tommy Robinson are completely isolated, all of them are so far from the core EU cluster as to be essentially disconnected).
Figure 6b. Graph displaying the network of Facebook pages liked by the pages associated with the alt-right in the EU/UK connected through the likes between them.
When we zoom in on the core of the EU/UK network the publishing house Arktos is clearly the central node (Arktos was also connected to the alt-right core, see figure 4). Upon closer inspection, we can identify a link the presence of a French a sub cluster in on the left, around Guillaume Faye’s archeofuturism movement (a radical offshoot that separated from French new right, itself represented by Alain de Benoist at the top), a Scandinavian cluster on the bottom around Daniel Friberg, and a neotraditionalist cluster (featuring Gornahoor who featured prominently in the alt-right core as well).
Figure 7. Graph displaying the three networks above combined. http://bit.ly/2vbSV3y
When combining the above networks, we can clearly see the isolation of two clusters: that of the manosphere centred around A Voice For Men (purple on the left), that seems to have few links with the rest; and the cluster around Arktos, which is only linked via the cluster associated with Jack Donovan. This network hints at the relative isolation of the conspiracist alt-light (centred around Alex Jones) on the one hand, and both the European cluster and the alt-right core on the other.
1. The Alt-right core’s significant others.
Who do the alt-right @mention?
Starting from a list of Twitter handles corresponding to the alt-right core (save those accounts that have been suspended - see footnote 1), we interpreted an @mention of another Twitter user as signifying those whom the core considers important, i.e., their significant others. Which other Twitter handles do the entire core mention (mentioned by all 8 members), do most of the core mention (7 of 8 members), many of the core mention (6 of 8 members) and so forth?
Alt-right core’s significant others according to a ‘Belonging’ metric
In effect we treat an @mention as a vote of belonging (or relevance) by the core, and the greater number of core mentions the greater the belonging of the collective @mentioned. Thus the users (@mentioned) who are mentioned by all of the core accordingly would belong to the core (100%), and those mentioned by most would have a high belonging metric (88%, 75%, 63% and so forth). (Note that not all Twitter accounts mentioned by the core belong to it, for the alt right core also mentions its targets (such as @splcenter). Thus @splcenter is relevant but does not belong.)
Figure 8. The Alt-right’s significant others on Twitter according to a ‘Belonging metric’. Users mentioned by all of the alt-right core, most of the core, many of the core, etc. July, 2017.
2. The Alt-right core’s audience.
Who @mentions the Alt Right? Does the Alt Right have an audience beyond itself?
Figure 9. The “short tale” of new alt-right core audience members on Twitter, July, 2017. (insert bit.ly)
From the @mention analysis above one is able to determine the extent to which the alt right core has an audience beyond itself, so to speak. Who @mentions the alt right core? Are they non-members of the core, suggesting an audience, or does the core just mention itself, suggesting a particular insularity? In the event, we found a relatively small chunk of new users (or mentioners) of the alt right core. The vast majority (more than two-thirds) of the mentioners of the alt right core is the core itself.
3. The Alt-right’s significant others according to @mentions (core, alt-lite as well as UK/EU).
Figure 10. If Figure 8 only showed the @mentions of alt-right core, then this graph displays the @mentions of Twitter handles from all three groups the alt-right core, alt-light and alt-right EU/UK and then spatialize them with node size signifying frequency and proximity to each corners signifying their relative use by that cluster.
The question here is the extent to which the alt-right, alt-lite and alt-right EU/UK share @mentions. Do they ‘speak’ of the same individuals, or of distinctive ones? Those nodes clustering closest to the subgroup are mostly mentioned by that group. That is, they have the ‘closest’ and most specific relationship with the group. Those nodes in the middle are mentioned by all three, and those between two subgroupings are mentioned by the two of them. Nodes may be mentioned by multiple groups, but be closest to one group, if the ‘strength’ of the tie is strongest (i.e., mostly mentioned). Generally one notes that there are actors that are specific to a group (e.g., the core, or the UK/EU), suggesting that balkanisation or at least differentiation. Those significant to all three groups (with large nodes) such as realdonaldtrump and gavin_mcginnis or two groups (with large nodes) such as lauren_southern and jackposobiec stand out. The group with the most specific, large nodes appears to be the UK/EU with such accounts as ezralevant and faithgoldy.
Alt-right hashtag information campaigning strategies
Once having then curated a larger seed list of authoritatively alt-right Twitter accounts (the core, their significant others and their new audience, so to speak), we then collected their hashtags. The larger the node the more frequently a hashtag is used. The closer the node to the group, the more specific or stronger the tie to that node (more usage).
Figure 11. Graph displaying the relative amount (proximity to three corners and node size) of hashtags used on Twitter, distributed between the three sets of, respectively, the alt-right core, alt-light and alt-right EU/UK.
From the hashtag clustering we note a series of alt right hashtag or campaigning strategies, enumerated below.
#tcot #nrx #altright
Issue pairing (with more extreme issues)
#Buildthewall #BanIslam (co-hashtagging)
The alt-right, we also noted, takes advantage particularly of events. Its ‘use’ of events may be highlighted by the Berkeley case.
From Event Spinning to “Event usage”
The Berkeley riots refer to a series of protests in April 2017 at the University of California in Berkeley. Some 1,500 anti-Trump protesters (anarchists, anti-fascists and other far-left radicals) came to protest the arrival of Milo Yiannopoulos, denying him to spread what they deemed hateful speech. Later that day the protests turned into a violent clash.
This case shows the strategy of exploiting certain events which is typical of the alt-right: it is a clear tactic of massively commenting and appropriating a certain event like Berkeley Riots framing it within their narrative. The alt-right actors conceive of themselves as vanguards, wanting to expose the real nature of the antifa protesters and wanting to expose the truth about the ruling supposed leftist ideology as a whole. They frame the Berkeley riots in a war-like narrative; thereby turning a predominantly cultural war aimed at discourse, which is fought out on the internet, into a physical battle against the representatives of political correctness, fought out on the streets. We could perhaps argue that this physical fight is actually a fight over who has the authority to define what free speech is.
They did not fail to notice the symbolism of the location of Berkeley, which was a leftist cradle for free speech movements. This framing of the battle it in terms of free speech, portrays their enemies, the antifa in this case, as anti-democratic and anti-free speech, ultimately being fascist. In doing so, they do an attempt at appropriating the discourse of free speech which was formerly associated with the left. The protesters claiming Trump to be fascist, are being framed here to be fascists themselves.
This case shows their ambivalent technique of appropriating former leftist politics, and turning it around. We could say that, the case of the Berkeley riots shows the appropriation of the countercultural progressive politics of the left. Thereby they, paradoxically, associate the left with the conservative or even fascist politics formerly associated with the right.
Alt Right Struggles
Disunity found among alt-right channels and featured videos
The YouTube analysis of the alt-right here concerns common channel subscriptions and featured content between alt-right members. Do alt-right members subscribe to each other’s channels? (Directionality of subscribing is available.) Do they feature each other’s videos? (Directionality of featuring is not available.) Here we note specific relationships between alt-right members. We also note what could be called disunity. Most alt-right members do not subscribe to each others channels, and far less so feature each other’s videos.
Figure 12. Shared subscriptions and featured content among the Alt Right on YouTube, July 2017.
Secondly, we looked more specifically into those videos that are particularly disliked. What’s there to dislike about the alt-right? The question refers to those who like/dislike videos, and comment upon them.
Figure 13. Top Alt-lite videos by dislike count, July 2017.
Alt Right core’s top disliked videos may be categorised as follows, with examples.
- Milo Goes Up in Flames
Internal, doubtful commentary
- What is the Alt Right?
- The Alt Right’s break up with Trump
- Black women attractiveness video
- The Orlando Shooting Was A False Flag
Figure 14. Top comments on Alex Jones’s video, The Orlando Shooting Was A False Flag. Note the top comments contest Jones’s narrative rather than affirm it.
On Facebook, the alt-right core’s most engaged with content is more extremist, the alt lite’s anti-establishment and the alt-right UK/EU counter-jihadist, thus suggesting a new (and significant) theme to the Alt Right spectrum (see Figure 1). On Facebook the inter-liked page networks for each of the subgroups reveals an insular alt-right core, an alt-lite revolving around Alex Jones, and an UK/EU networked centered around Arktos, with Tommy Robinson isolated. Given the specificity of the ties of this European new right to the alt-right, it could be called the new alt-right or the alternative new right. Note that there is a vast ‘new right’ across Europe not depicted, which includes a large counter-jihadist movement in Scandinavia (Norway and Denmark), Pegida in Germany, Identitarians in France and many others.
On Twitter the Alt-Right core has ‘significant others’, or those mentioned by 7 or 8 of the core, as indicated by a so-called belonging metric. The alt-right’s newly discovered audience, however, is relatively small, as the majority of those they mention are themselves. The alt-right has particular information campaigning styles, such as hashtag hijacking as well as hashtag pairing (which links or ‘pairs’ a conservative issue to one that is far more extreme) as well as a particular strategy of event spinning or ‘use’ such as Berkeley case, discussed above.
On YouTube we found emerging ‘alt-right struggles’ where there is a certain disunity among the alt-right as evidenced by the lack of shared channel subscriptions and featured content. There is also a great dislike for many of their videos, as shown by lists of ‘top disliked videos’ as well as contested commenting where the top ranked comments for certain videos are particularly negative, disavowing the content as well as the video-maker.
While the alt-right core may, itself, be a rather insular network, the alt-light is much more public facing and media savvy. And while we did not necessarily come up with a metric to effectively assess their influence, through their strategic use of media events on Twitter and through the enormous celebrity of Alex Jones, it is clear that the alt-right have a significant and growing reach into digital culture -- also see the DMI Summer School’s Youtube alt-right research project, and the Reddit research regarding overlaps with gamer culture. The EU alt-right appears to be a more mature and developed network than the alt-right core highly centred on the publisher Arktos, this suggests that a next step would be to study the content of this EU alt-right literature.
Setting aside whether and to what extent aspects of these ideas could or should be categorized as extremism, what we have observed is that the influence of a new set of right wing ideas online is real and can be seen to be spreading within, across and beyond the alt-right. This new set of ideas complicates former dichotomies between left- and right-wing ideas. As the case of the Berkeley Riots shows, the figures associated with the alt-right attempt to appropriate the counter-hegemonic language of the (New) Left. Ideas of counter-cultural transgression of established norms, non-conformism, radical free speech, anti-neoliberalism, anti-globalisation, workerism, anti-war, consciousness raising, vanguardism, and identity politics are being used against leftists and liberals themselves, thereby maintaining to be the only real radical alternative.
Furthermore, figures 6a/b show the presence of French Nouvelle Droite thinker Alain de Benoist, as well as Guillaume Faye. The latter was formerly associated with the Nouvelle Droite, but later came to criticise De Benoist. Both De Benoist and Faye have been heavily influenced by Italian communist theorist Antonio Gramsci. These ‘Gramscians of the right’ took from Gramsci the idea that the proletarian struggle should have a prime focus on the level of culture (although Faye to a lesser degree, as he criticises De Benoist’s interpretation of Gramsci in purely cultural terms. Instead Faye calls for the importance of "concrete political forces” as well). Alt-right strategies on the whole seem to share exactly this principle of ‘metapolitics,’ making use of ‘infowars' aimed at infusing society with ideas and rhetoric, so as to challenge hegemony.
This counter-intuitive composition of elements seems to question left/right contrarieties, suggesting a need for further inquiry into the upsurge of these new set of right wing ideas so intricately linked to leftist counter-cultural movements. How are we to understand the substantial influence of the alt-right's ‘culture war’ against so-called Social Justice Warriors and Cultural Marxists, while their tactics as well as ideas share so many resemblances?
Another point worth raising here, concerns the parallels the alt-right shows with populist movements. The term 'alt-right' has proven to be an effective popular denominator, uniting very divergent groups and individuals. The idea of the alt-right - ambivalent as it is - has become an umbrella term for an amalgam of divergent aims, goals, ideas, and demands; so much so that self-branding has become paramount to the alt right (see for example the popular hashtag #altrightmeans, or the numerous youtube movies titled “what is the alt-right?”). Such popular identifications with one prominent name, is central to any populist articulation, by bringing together a broad array of demands. The extensive use of 'basket of deplorables’ (formerly a derogatory term, now used as reappropriated self-identification), pertains to the idea of being an underdog and an outsider, set off against the establishment. These supposed established groups and ideologies occupy a chief focus in the alt-right discourse. The list of enemies is plentiful and diverse, ranging from Social Justice Warriors and Cultural Marxists, to Jews, Cuckservatives and Normies; but all are supposedly responsible for the establishment in some sort of another. This antagonist logics of the underdog versus the establishment is, again, key to any populist identification.
As such, it may prove to be fruitful to analyse the alt-right through a perspective of populism - not only because it could provide a deeper understanding of the development and tactics of the alt-right, but also, conversely, the alt-right could potentially expose something about populism itself: Populist politics in general are increasingly dependent on social media, and it could very well be reasoned that the alt-right is a certain configuration of populism that is fundamentally Web-based, and, as a result, is shaped by the affordances of the Web. Although such observations are preliminary and require more research, the alt-right could, arguably, offer a case in point to understand these specific affordances, looking for example at the role of trolling, transgression, online culture/info wars, DIY-propaganda, free speech, memes and the dynamics of Web-based crowds more generally in the shaping of popular identifications.
4chan /pol/ Wikipedia: Mapping the issue topics of 4chan’s Politically Incorrect
Summary of Key Findings
Nuremberg trials Nut rage incident Nuwaubian Nation Nyctixalus moloch O Canada O. J. Simpson murder case O.F. Mossberg & Sons O'Reilly Oakland Ebonics resolution Oakville Assembly Oakville, Washington Oath of vengeance Oban Obelisk of Theodosius Obergefell v. Hodges Obersalzberg Speech Obesity in Canada Obesity in Mexico Obesity in Nauru Obesity in the United States Objections to evolution Observation mathématique de la pyramide de Khéops Observer effect (physics) Obsolete Russian units of measurement Occam's razor Occasionalism Occitania (administrative region) Occupation of Constantinople Occupation of Poland (1939–45) Occupation of the Malheur National Wildlife Refuge Ocean acidification Ocean disposal of radioactive waste Ochre Ocoee Whitewater Center October Crisis October Revolution October surprise October Surprise conspiracy theory
Even while the imageboard 4chan is seen by some as the “rude, raunchy underbelly of the internet” (Fox News), the amalgamation of its anonymous users has caused it to grow into a considerable political power. Its /b/ board has been one of the main hubs for trolling, shitposting and general obscurity. In its early days, 4chan found political resonance through the tech-savviness of mostly leftist trolling movements, later popularised under the term "Anonymous", derived from the platform's anonymous users (Philips 58). However, over the course of recent years, the website’s politically-oriented /pol/ board has seen an influx of (alt-)right winged-support, creating an obscure mesh of anti-SJWs, conspiracy thinkers, Pepe’s and political incorrectness (Burton). This shift was arguably set in motion by Gamergate, the gaming culture controversy that “politicized a broad group of young people, mostly boys, who organized tactics around the idea of fighting back against the culture war being waged by the left” (Nagle 24). To scrutinize 4chan as a site for the emergence of political thought and global movements, it is necessary to identify which topics resonate within the imageboard’s community. One way of doing so is by identifying which Wikipedia articles 4chan’s users link to. This project attempts to visualise the issue topics of /pol/ through creating a piece that depicts the titles of /pol/’s linked Wikipedia titles.
2. Initial Data Sets
A collection of around 9 million posts and comments was acquired from a separate research institute (Hine et al.). These posts were made between June 28th and September 12th, 2016. The data consisted of opening posts as well as comments made on these posts. The comments were almost exclusively from 4chan’s /pol/ board, with a very small fraction of the posts from /int/, a board on exchaning foreign culture, and /sp/, the board concerned with sports. See Hine et al. for a more detailed description. The data consisted of JSON-lines within a Postgres data dump, so some processing had to be done to make it readable, as described in ‘Methodology’.
3. Research Questions
Technically, making the data manageable proved to be rather diffucult. The dataset contained the posts in a Postgres database dump, that itself contained lines with JSON objects. With a Perl script, this file was converted into a large JSON file. This JSON file generated was too big to load into memory. The file weighed in at about 4 gigabytes, which also added the overhead of being slow if data were to be looked up frequently as it would have to be looped through completely. Splitting it with programs like HJSplit would result in breaking the JSON format, which would corrupt the data. Libraries like ijson in Python exists to handle large JSON files, but the library expects the user to know of the exact key to be looked up, which in our case was not possible, since the keys were user IDs and they weren’t exactly in a continuous range. As a result we had to come up with a different approach.
This resulted in the creation of a library that would iterate through the entire file in a sequential way and parse the JSON formatted data and convert it into Comma Separated Values (csv). The data were broken up at around 50k records, to allow for resuming the operation if there was an error and it did not have to restart from the beginning. Breakpoints were pre-calculated and the entire process was parallelized in order to leverage the (limited) computing resources that we had access to. The Python script called ‘4chanextractor’ (Summer School scripts) was made to do this task. It was then run on 3 computers (2 laptops and a desktop), with each computer running the script twice with different starting and ending points for 2 days to process the entire JSON dump and have them in separate csv files. Each run of the script took about 10 hours on a modern Intel i7 core (at the time of the writing) to complete their chunk processing (and was perhaps the most time consuming part of the dataprocessing step). These CSVs were then easily processed using optimised database management library, like Pandas, and new separate and single CSVs were created for each requirements, for example for the Wikipedia links, the relevant comments, YouTube links, etc. Some posts and comments contained raw HTML such as <a> tags, which were removed with another Python script (Summer School scripts). The stripped comments were stored in the the column ‘com’. The originals were stored in the ‘raw_com’ column. As such, a ‘clean’ csv with the following information was produced:
- no: Post Number
- resto: Replying to post number
- now: Date and time, MM/DD/YY HH:MM in EST/EDT timezone
- name: Name
- id: post ID
- capcode: Type of user (e.g. admin, mod, none)
- country_name: Country name of the IP address of poster
- sub: Subject of post
- com: The comment body,
- replies: The number of replies (only applies if it’s an opening post (OP))
- capcode_replies: array of capcode type and post IDs
- last_modified: UNIX timestamp of when the post was last modified
- tag: The thread tag
- semantic_url: URL of post in semantic data
- raw_com: The original post in raw HTML, as they were initially gathered.
In order to collect the Wikipedia data, another Python script was written that uses the Wikipedia Python API
to look up which comments contained a link to a Wikipedia article, and to extract the titles of the referred Wikipedia articles in these respective posts (Summer School scripts). For comments containing multiple links in the same comment, duplicate rows were generated with the same comment body but different links, in order to make the referencing of each individual links easier. Since the main concern for this project is the analysis of the Wikipedia links, we extracted only unique links, which was done by using the group function of the Python Pandas library on the Wikipedia URL column. This also provided the information on how many times a URL was quoted by the user. Subsequently, duplicates were counted in order to produce an engagement metric, but this was not used for this project. Ultimately the script saves the extracted data as a new csv in the same folder as your source file. The resulting csv contains:
- titles: The title of the referred Wikipedia article
- urls: The URLs referring to the Wikipedia article
- com: The actual comment or post, containing the link(s)
- country_name: country name of the user’s IP address
- now: timestamp of when the comment or post was posted
Since a number of extracted URLs contained specific characters, which were originally encoded by both percent-encoding as well as unicode, the titles in the csv file were cleaned using a URL decoder/encoder
and a manual decoding using a Find and Replace function on LibreOffice
In order to produce the final visualisation, the decoded title column was copied into Sublime Text Editor where the returns were substituted by four spaces. The produced alphabetically arranged text containing over 13 000 titles was copied onto an A0 format, formatted using a 6pt size Lekton font and 1.1 spacing using Adobe Indesign. The project’s title and the names of the team members were added. The final product was then printed. The same text was also used to produce a web version (forthcoming). The exact same string was used, together with CSS’s pre-wrap function so the spaces were not deleted by the browser’s rendering of the HTML file. A
Image 1: A sample of the visualised links
In all there were about 26.000 wikipedia links extracted from the 9 million initial comments. As a first version, this project depicts the referenced Wikipedia titles in an artful manner in order to invite initial exploration, and as such does not present any findings. However, even this minimal representation gives some insight into the issues that are prevalent within /pol/. A quick filtering of the titles reveals some themes:
- 214 articles with ‘battle’ in the title
- 270 with ‘war ’ in the title
- 106 articles containing ‘countr’
- 62 articles containing ‘israel’
- 153 articles containing ‘america’
- 83 articles containing ‘relig’
- 33 articles containing ‘god’
- 92 articles containing ‘jew’
- 58 articles containing ‘christian’
- 25 articles containing ‘muslim’
- 96 articles containing ‘islam’
- 8 articles containing ‘hindu’
Also, many articles seem fairly obscure or out-of-place at first sight. A quick sample provides titles such as:
- “Contest to kill 100 people using a sword”
- “Chocolate-coated marshmallow treats”
- “Donald Duck Party”
- “Crab mentality”
- “Cheddar Man”
- “Nut rage incident”
- “Deep frying" and "Deep fried Mars bar”
As one of the team members described, the 4chan /pol/ Wikipedia often “reads like a Radiohead song”. Though an art piece at first, this project indicates it could benefit greatly from further qualitative research, mainly through investigating in what context the Wikipedia articles were linked and identifying recurring themes. However, a first inquiry already reveals the particularities and obscurities of 4chan’s /pol/ board, and through its referenced Wikipedia articles, some of these characteristics can be captured and (artfully) presented as a representation of themes and issues.
Suggestions for the future include producing a web version with a textbox with the comments in which the respective Wikipedia article was linked. Additionally, we could have used a more automated technique for decoding the fetched Wikipedia titles that were collected by the Wikipedia API. Also, we should have started working by decoding URLs rather than the titles, since our attempt to retrieve the working decoded URLs from the titles proved to be a struggle in the later steps of research. Ideally, the cleaning of the data would include these steps: (1) decoding all symbols in URLs, (2) extracting the titles from decoded URLs, (3) removing and counting duplicates.
If 4chan were indeed to be understood as a ‘cultural juggernaut’ (Philips), identifying the topics discussed on /pol/ can reveal the fringe issues that might grow into more widespread theories. The printed ‘4chan Wikipedia’ discussed here tried to visualise the issue topics of this influential imageboard. As said above, this project was merely an attempt to create an art piece that provides a window into the obscurities of the board, but gave considerable incentive to conduct further analysis with this dataset. Specifically, the Wikipedia articles show the board's obsession with war, history and religion (particularly on Judaism and Islam).
Burton, Tara Isabella. “Apocalypse Whatever.” Real Life Mag. 12 Dec 2016.
< http://reallifemag.com/apocalypse-whatever/ >
Fox News. “4Chan: The Rude, Raunchy Underbelly of the Internet.” Foxnews.com. 8 Apr 2009.
< http://www.foxnews.com/story/2009/04/08/4chan-rude-raunchy-underbelly-internet.html >
Hine, Gabriel Emile, Jeremiah Onaolapo, Emiliano De Cristofaro, Nicolas Kourtellis, Ilias Leontiadis, Riginos Samaras, Gianluca Stringhini, Jeremy Blackburn. “Kek, Cucks, and God Emperor Trump: A Measurement Study of 4chan’s Politically Incorrect Forum and Its Effects on the Web.” Association for the Advancement of Artificial Intelligence, May 2017.
Nagle, Angela. Kill All Normies. Winchester: Zero Books. 2017.
Philips, Whitney. This Is Why We Can’t Have Nice Things. Cambridge: MIT Press. 2016.
Summer School scripts. Github.
Cucks, SJWs and Based Pedes: Mapping the language of Reddit's Alt-Right Communities
Reddit, a social-sharing site, link aggregator and community of communities, is at the time of writing the fourth-most visited website in the USA, behind only Facebook, Google and YouTube . It is home to, among myriad other communities, The_Donald, a subreddit run and populated by some of Donald Trump's more vocal supporters. As of July 2017, it has over 460,000 subscribers, and it has grown enormously since its inception in late 2015. Among other features of note, it is probably the largest unified Alt-Right community on the internet, hosting users and elements from all aspects of the movement including the Manosphere, anti-progressive gamergaters, anti-globalists, white nationalists, and so on.
We wanted to use digital methods to understand first how the identity of The_Donald formed, and second the extent to which T_D - and the Alt-Right more broadly construed - can be considered a unitary phenomenon, as opposed to a set of loosely interlinked groups and communities brought into alliance through a common goal and vernacular. This subproject attempted to understand the ways in which the vernacular of The_Donald had developed and changed over time. In particular, we looked at the word "cuck" from its emergence on Reddit to present in an attempt to understand the formation of a core group identity on The_Donald, before going on to track the co-occurrence of different words which represented various aspects of the identity of The_Donald.
2. Initial Data Sets
A dataset of all Reddit comments since 2007 (initially 1.7 billion in 2015, now many more) was uploaded by a third party to Google's BigQuery platform. This dataset was both queried whole and partitioned off into multiple chunks for efficiency purposes. The data contained comments, but not initial posts (though these are also available). Metadata included the body of the comment, the author's username, timestamp (epoch time), subreddit ID, score (upvotes vs downvotes) and several other categories.
3. Research Questions
1. How did the word "cuck" come into common parlance in The_Donald, and in what ways has its meaning shifted over time?
2. To what extent can the Alt-Right, embodied in The_Donald, be understood as a unitary phenomenon through its linguistic mores?
The group had little prior experience of BigQuery or the Reddit dataset, and so it took some time to refine the methods by which the data could be queried effectively. Eventually, several novel methods were developed. Detailed recipes can be found in the Summer School 2017 Protocol document.
1. In order to track concepts (using individual words as proxies) across Reddit over time:
We used the following script to extract a count of how often the keyword occurs in different subreddits in a given period, ranked by subreddit.
count (*) count,
LOWER(body) LIKE '%sjw%'
This uses the fh-bigquery:reddit_comments dataset, which is publicly available at https://bigquery.cloud.google.com/dataset/fh-bigquery:reddit_comments.
In addition, Tim Squirrell has created monthly datasets of pre-2015 comments, which are only available annually in the dataset above. These datasets are available here as “allcomments_1201” through to “allcomments_1412”. https://bigquery.cloud.google.com/dataset/alt-right-intelligence:Reddit
This was done month by month, with the resulting files extracted in .csv format. From there, Raw Graphs was used to produce visualisations.
2. In order to map the "in-group" language of The_Donald:
We extracted the most used terms (which are not used by other common subreddits):
SELECT word, COUNT()
SELECT SPLIT(LOWER(REGEXP_REPLACE(body, r'[\.\",:()\[\]|\n]', ' ')), ' ') word
AND author NOT IN (SELECT author FROM [fh-bigquery:reddit_comments.bots_201505])
WHERE word NOT IN (
SELECT word FROM (
SELECT word, COUNT()
SELECT SPLIT(LOWER(REGEXP_REPLACE(body, r'[\.\",:()\[\]|\n]', ' ')), ' ') word
WHERE subreddit IN ('movies', 'politics', 'science')
GROUP EACH BY 1
ORDER BY 2 DESC
GROUP EACH BY 1
ORDER BY 2 DESC
Next, we used a word association script:
SELECT a.word, b.word, c, ratio
SELECT a.word, b.word, c, ratio, RANK() OVER(PARTITION BY a.word ORDER BY c DESC) rank
SELECT a.word, b.word, COUNT() c, RATIO_TO_REPORT(c) OVER(PARTITION BY b.word) ratio
SELECT word, id
FROM [alt-right-intelligence:Reddit.2016_04_LoL_TD] a
CROSS JOIN (SELECT word FROM (SELECT LOWER('sjw') word)
,(SELECT 'common' word),(SELECT 'when' word)) b
WHERE author NOT IN ('AutoModerator')
AND LOWER(body) CONTAINS word
AND subreddit NOT IN ('leagueoflegends')
) a JOIN EACH (
SELECT word, id FROM (
SELECT SPLIT(LOWER(REGEXP_REPLACE(body, r'[\-/!\?\.\",:()\[\]|\n]', ' ')), ' ') word, id
WHERE subreddit LIKE 'The_Donald'
AND REGEXP_MATCH(LOWER(body), 'the|common|when')
AND NOT word IN ('the','and','that')
GROUP EACH BY 1,2
GROUP EACH BY 1,2
WHERE ratio BETWEEN 0.25 AND 0.95
AND a.word NOT IN ('common','when') AND b.word NOT IN ('common','when')
ORDER BY a.word, ratio DESC
This was repeated for the words "cuck", "based", "pede", "SJW", "4chan", "pepe", "kek", "maga" and "globalist".
The resulting data was used to produce a word-association network with the Halfviz interface
Image 1: animated GIF of the most-used words in The_Donald by month
The above gif illustrates the preoccupations of commenters in The_Donald on a month-by-month basis. What should become clear with enough time examining the image is (i) Donald Trump himself becomes less prevalent in the discourse of the subreddit; and (ii) certain words (e.g. "cuck", "kek", "pepe") become more common over time.
Image 2: incidence of the word "cuck" across most relevant
subreddits, August 2014-May 2017 (full size image available here
*where "most relevant" is defined as those subreddits where "cuck" was used more than 200 times in a given month.
Image 3: "cuck" from August 2014 to May 2017, normalised distribution
The links below are the word association graphs for The_Donald, produced in HalfViz
April 2017: http://arborjs.org/halfviz/#/MTE0Mjk
March 2017: http://arborjs.org/halfviz/#/MTEzOTQ
February 2017: http://arborjs.org/halfviz/#/MTEzOTU
January 2017: http://arborjs.org/halfviz/#/MTEzOTY
December 2016: http://arborjs.org/halfviz/#/MTEzOTc
November 2016: http://arborjs.org/halfviz/#/MTEzOTg
October 2016: http://arborjs.org/halfviz/#/MTEzOTk
September 2016: http://arborjs.org/halfviz/#/MTE0MDA
August 2016: http://arborjs.org/halfviz/#/MTE0MDE
July 2016: http://arborjs.org/halfviz/#/MTE0MDI
June 2016: http://arborjs.org/halfviz/#/MTE0MDM
May 2016: http://arborjs.org/halfviz/#/MTE0MDQ
April 2016: http://arborjs.org/halfviz/#/MTE0MDU
March 2016: http://arborjs.org/halfviz/#/MTE0MDY
February 2016: http://arborjs.org/halfviz/#/MTE0MDc
January 2016: http://arborjs.org/halfviz/#/MTE0MDg
The simple word clouds above indicate the preoccupations of The_Donald in any given month, with Trump himself the focus for some of 2016 before becoming less important as the group's core identity came to the forefront. The group focussed first on Trump's Republican rivals, before turning its gaze on Hillary Clinton, and then towards the mainstream media after Clinton was defeated. Many of the words which are most prominent in the subreddit's language are slurs or other forms of invective, and it is telling that this group communicates in ways that appear to be deeply tinged by bitterness and animosity.
It quickly became evident over the course of this subproject that The_Donald had developed a very particular vernacular, as can be seen in any of the halfviz networks above. Moreover, these networks appear to show the development of a core "Trumpist" group identity which is then surrounded at the peripheries by anti-globalist and anti-progressive narratives. The salience of these narratives change from month to month based on current affairs, for example "Macron" becomes a link between "globalist" and "cuck" in mid-2017, reflecting the preoccupation of the group with the French election. Based on this observation of the peripherality of some themes to the core group identity, we used the "subreddit algebra" tool
to examine the overlaps between commenters in The_Donald and certain other kinds of group. What we found corroborated the hypothesis that there are a number of different groups of commenters in The_Donald, characterised by their membership of other subreddits. The anti-globalists are not the same as the 4chan shitposters, and the KotakuInAction
gamergate users are not the same people as the white nationalists.
The word "cuck" acts as a binding glue between certain parts of the community. More detailed discussion of the analysis of "cuck" can be found here
, but the essential story is that it emerged in its current form from 4chan during gamergate, before migrating to Reddit through the /r/4chan subreddit and then making its way to KotakuInAction
, followed by /r/CoonTown (an explicitly racist subreddit) where it picked up more racial connotations. After CoonTown
was banned, it continued to be used in other alt-right type communities, but it went "mainstream" in February 2016 when The_Donald exploded in popularity after Trump won the New Hampshire primary race. It has since become a core part of T_D's vocabulary, and its lack of popularity in non alt-right subreddits would suggest it exemplifies the in-group language of this community.
The use of BigQuery
to analyse Reddit through the lens of the social sciences and cultural studies is new. This is the first time that the formation of political movements on Reddit has been tracked through analysis of the language of those groups, and whilst it has produced a number of interesting findings there is still much room for improvement. In particular, the scripts used to query the dataset could be refined to produce more useful results, and larger queries could be more effectively handled by groups with access to somewhat more powerful computers.
However, what is evident is (i) that this is a promising area for further study, as Reddit is only increasing in size whilst remaining open-source and open to data-driven scrutiny; (ii) that since Reddit continues to provide a platform for alt-right groups, this is both an effective and important way of studying the way these groups form and how their language diffuses out from them; and (iii) The_Donald itself deserves more scrutiny, as it would appear based on the findings of this study that its very existence is responsible for the propagation of hate-filled language into the rest of Reddit, and potentially into wider culture through these channels.
Exploratory Assessment of Google Vision API "Web Detection" Module for Making Sense of Memes
Summary of Key Findings
The exploratory assessment revealed relative usefulness of Google Vision API “Web Detection” feature for annotating large visual datasets according to specific subjects of interest. Following the general annotation of all an 8,762 images dataset, closer observations were made regarding the accuracy of the labels “Pepe the Frog” and “Hillary Clinton”. Automatic annotations were compared with human annotations regarding these two cases. The API’s performance was considered insufficient for fetching all the occurrences of a given subject. However, the accuracy of the positive identifications was considered good (80% of “true positives”), to the extent that it can be a good aid for human annotation or for quickly overviewing the overall composition of the corpus. Results also include an improved version of the Memespector script for querying other modules of the Google Vision API.
The subproject was initially oriented towards the study of memes in relation to the meanings emerging from their pragmatics: the way meaning is formed and transformed across the use of memes; ways of observing this process by a conjoint analysis of images and associated texts; categorization of memes, ways of stratifying the mass of observed images; etc.
A series of contingencies forced the subproject to be reframed, however. First, due to time restrictions, as it was carried out only in the first week of the Summer School (which was particularly short in respect to the program of lectures in the first days of the event). Second, due to team restrictions, as only one member was totally focused on this, whereas others joined either for particular tasks or as facilitators working across different subprojects. Finally, due to the choice to pursue a path that was still technically challenging and which required tool adaptation and a time-consuming processing of the whole image dataset.
Finally, the subproject was particularly oriented, in this week, for a tryout of Google Vision API “Web Detection” module. It is one of the eight modules composing the API, specialized in detecting “Web Entities”, which can be used as more precise labels identifying specific entities present in the image (e.g. “Hillary Clinton” instead of “woman” or “face”). It was seen as potentially more useful for the approached dataset and research questions, than the “Label Detection”, which had been previously applied to the dataset, from its implementation in Berhard Rieder Memespector script. Assessment of this previous experience – as reported by the facilitators – was that it was too generic for this case.
Example comparison of “Label Detection” and “Web Detection” modules results:
Label detection results:
Pc Game 70%
Computer Wallpaper 64%
Cg Artwork 53%
Web detection results:
Donald Trump 15.4942
Vladimir Putin 7.0778
Crippled America 1.0738
Donald Trump presidential campai... 0.52606
The subproject then produced, as main contributions: an overall assessment of the “Web Detection” feature from a case study oriented by the dataset (presented in this report); and an improved version of Memespector script with more options for activating different modules of the Google Vision API.
2. Initial Data Sets
The dataset used in this assessment was comprised of 8,762 posts collected from the “God Emperor Trump” Facebook page, using Netviz, between 19th of December 2015 and 14th of December 2016. While extensive data was available for each of these posts, only their images were used in the research.
3. Research Questions
Initial research questions were mainly related to the overall proposal of the subproject titled “Making Sense of Memes”. Those applicable to the approached dataset included:
Can we identify a single “genre” of meme, such as for example Pepes?
How do we study memes when their meanings are ambivalent and they are constantly “mutating”?
Can we, perhaps, derive the meaning of memes by studying the comments associated with them?
Which memes have the most currency and in relation to particular political events?
If memes are weapons, then who are they targeted at?
While the research had these questions on its horizon, the actual course of the research, conducted in the first week of the Summer School, led it to be contained within an initial exploratory assessment of Google Vision API’s “Web Detection” module. In this context, the questions were more technically oriented:
What features is Google Vision API “Web Detection” module able to describe within the approached dataset?
How accurate is Google Vision API “Web Detection” module in identifying subjects of interest across the dataset?
What uses can be made of the tool’s results?
The research applied Google Vision API “Web Detection” module, which is one of eight modules provided by the tool. This module provides different result types for the image processing query, broadly divided between a list of ‘web entities’ related to the image and URL lists of matching, partially matching and visually similar images found elsewhere on the web.
The approach focused on the ‘web entities’ list, which was considered – in preliminary results – more useful for the overall research questions. Google provides little documentation or definition for what ‘Web Entities’ are, except that they match items included in its ‘knowledge graph’, which fuels its search engines and other types of intelligence tools. In that respect, the entities seem to relate to relatively distinct semantic items which may be identified in relation to processed content (visual or otherwise).
The research thus consisted of these procedures:
Customizing the Memespector script for fetching results from the “Web detection” module.
Considering the large amount of data generated by this module, as well as the relatively high cost of its use, the script was first adapted to store the results in a MySQL database. However, this later revealed to be an overkill due to the additional effort for combining the different tables of the database in producing significant analysis. The current version of the script outputs the result to a CSV file (as Memespector already did for the “Label Detection” module).
Initial tryout run of a subset of 50 images through the Google Vision API “Web Detection” module.
Results revealed to be more specific than the “Label Detection” module, as predicted by the initial hypothesis.
One of the “Web Entities” identified by the API was “Pepe the Frog” – a popular meme that was already a subject of interest for the research. This made the Web Detection approach significant for the subproject as it would potentially allow for the mapping of the meme through time.
Parallel to (B), a taskforce of 6 people went through the whole dataset marking the images in which they identified the “Pepe the Frog” meme.
This was pursued through a Google Spreadsheets using the “IMAGE()” formula, which shows a preview of an image using its URL. Cells contained thumbnails of the images and the mark for identified “Pepe the Frog” was placed in an adjacent cell.
The whole dataset was ran through the Google Vision API, collecting the results to a MySQL database
This took about 10 hours and was particularly problematic due to the absence of a remote server or desktop computer for running this over night. Each image took 3-5 seconds to be processed by the API.
The results were queried for images marked as related to “Pepe the Frog”. The results were compared to the manual annotation results.
Manual annotations were checked for false positives when automated annotation indicated a positive mark mismatching with a manual negative.
Results were queried for images marked as related to “Hillary Clinton”. The results were manually checked for consistency.
A random subset of 1,006 images of the whole dataset (11.45%) had the automated markings manually verified also using thumbnail previews on Google Spreadsheet, as used in (C).
The manual verification was done by a sole researcher and, importantly, it was not manual annotation as done with Pepe but, rather, a verification of the automated markings, which were marked as TRUE or FALSE.
The manual and automatic annotations were compared for the indicated subset.
Overall, 6,710 entities were found in the whole dataset, comprising 43,566 links between images and entities, on an average of 4.96 entities per image. Very mixed types of entities, both generic ("image", "face", "United States of America"), and specific ("Hillary Clinton", "Barack Obama 'Hope' poster", "Trump: The Art of the Deal" Book).
Entities included typical alt-right vocabulary, such as “kek” and “cuckservative”. There were peculiar entities such as the long-sentence-named: "First they ignore you, then they laugh at you, then they fight you, then you win". Clearly, it is a non-structured, non-hierarchical, non-exclusive, form of classification and organization of content.
As expected, many entities reoccurred in different images. Top reoccurring entities were: “Donald Trump”, “Meme”, “United States of America”, “Image”, “United States presidential election, 2016”, “Donald Trump presidential campaign, 2016”, “Hillary Clinton”.
Tracking “Pepe the Frog”
Tests comparing Google Vision API “Web Detection” results with manual annotation of the whole dataset.
| || |
Intersection of manual and auto positives
False positives (compared to manual)
False negatives (compared to each other)
Percentage of actual entities (compared to each other)
Reliability of positive marks (compared to manual)
Google Vision examples of false positive cases (The Simpsons were recurrent):
Google Vision examples of false negatives (difficult to understand the reason for the negative mark):
Human annotation false negatives that were caught by Google Vision:
Tracking “Hillary Clinton”
Google Vision API “Web Detection” assessed by manual verification of 1,006 items (11.45%) of the dataset.
False positives (manually checked)
False negatives (manually checked)
Percentage of actual entities (considering false negatives)
Reliability of positive marks (considering false positives)
Web detection scores
Google Vision API presents a score for each “Web Entity” detected. There is no documentation regarding its meaning and it is certainly not intuitive. For example, “Pepe the Frog” scores range between 0 and 1000, while “Hillary Clinton” scores range between 0 and 20.
However, there seems to be a correlation between “False Positives” and the obtained score, which can be visualized below. RED marks indicate a false positive and GREEN marks indicate a true positive. Clearly, low-scoring positives are more likely inaccurate. Therefore, it could be possible to find optimal thresholds for minimizing the probability of false positives in the analysis.
Results showed relative consistency considering the two case studies of “Pepe the Frog” and “Hillary Clinton” identifications. This is shown both in the percentage of actual entities caught by the API algorithms, oscillating around 50%, and in the reliability of the positive marks (probability that the marking is accurate), which runs around 80%.
The results are certainly limited considering the number and variety of “Web Entities” that were tested. This is particularly important taking into consideration that other entities are not visual in nature, but are rather more conceptual, such as “Liberalism” and “Alt-Right”, which were also found in the approached dataset.
From the results of this brief study, however, there are already some relevant findings. For instance, it seems clear that the Google Vision API Web Detection tools is insufficient for cases in which it would be crucial to fetch all the occurrences of a given ‘entity’, since half of those occurrences are not positively identified. However, it seems to serve as a second aid to human annotation, being able to identify false negatives in their annotation.
Also, the reliability of the postive markings (80%) – especially considering that this can be improved by the consideration of the detection score – make the API useful for forming non-comprehensive subset around particular topics.
Overall consideration of the API results also shows that it is useful for mapping the topics covered by the dataset, which may be unforeseen (e.g.: “The Killing of Harembe” was a significant entity identified).
Findings in this brief research effort may contribute for cautious and critical uses of Google Vision API as a research tool for visual methodologies. It provides insight into the functioning and reliability of the tool. Moreover, it indicates paths for future assessments. Particularly, there is the indication of need of further assessments regarding different types of “Web Entities”, which may be harder to consider with regards to their non-visual conceptual nature. Also, it was shown that further investigation of the detection scores are needed in order to better interpret the obtained results and to improve the overall reliability of the tool.
Among the possible unfoldings of the use of the tool, it is possible to suggest that its results may foster the building of “Co-entity networks” for a relational analysis of the approached topics. Also image networks or bipartite image-entity networks can be built for clustering the dataset into significant groupings. Finally, it provides the possibility of observing the tracking of entities over time. All of this, of course, taking into consideration the observed limitations of the results.
LARPing as a Political Practice
The Emergence of the Superhero Meme “Based Stickman” as an Energizing Mascot for the Alt-Right
Summary of Key Findings
.The perspective of fiction confirms its fruitfulness as a theoretical framework to investigate so-called “post-factuality”.
.The notions of “performance” and in particular “performance art” seem key to articulate in this sense a possible understanding of the Alt-Right’s cultural milieu.
.”Based” is the new “woke” → deeper understanding of the term “based” in the context of a possible Empirical Dictionary of the Alt Right that studies Alt-Right’s jargon in its formation and negotiation on platforms such as Reddit & 4Chan.
.The Alt-Right’s media strategy presents striking similarities with some aspects of Ku-Klux-Klan’s aesthetics.
.The Alt-Right is an activist avant-garde that re-appropriates tactics typically associated with left-wing activism.
.This sub-project also studied how a fictional character such as a superhero is created in the context of participatory culture.
On March, 4th 2017, commercial diver Kyle Chapman headed to Berkeley (California) for a pro-Trump rally promoted as “March 4 Trump”. He was wearing a black hoodie, a Nike baseball helmet, shin guards, protective googles, a respirator, a shield with a US flag’s sticker and a solid-wood stick. As known1, the rally degenerated into clashes between pro-Trump and anti-Trump’s supporters that were holding a rally nearby. During the violent confrontation, Chapman hit on the head with his stick an “Antifa”, Alt-Right’s jargon to describe militant antifascists. The moment was captured by a bystander on a video subsequently uploaded on YouTube. Soon thereafter, the still depicting Chapman in the act of beating the anti-Trump protester’s head was made into a meme that started to propagate on 4Chan and Reddit. Simultaneously, a more complex narrative around this superhero begun to be articulated through a series of videos on YouTube. It described Chapman as a superhero called “Based Stickman” that fights against the odious Antifa on behalf of American patriots. In specific, one video2 became viral, stabilizing a definitive story about Based Stickman’s origins. A new superhero was born .
This sub-project tells the story of Based Stickman individuating him as a nodal point for a possible understanding of American Alt-Right’s cultural milieu from the perspective of fiction. In this regard, it may be framed in an overall theoretical project that attempts to analyze so-called post-factuality as a form of “fictionality”. Particularly, in the Based Stickman’s case, the practices of LARPing (live action role playing) and cosplaying (dressing up as favorite fictional characters) seem key to a conceptualization of the porous zone between fiction and reality where Alt-Right’s actors thrive.
2. Initial Data Sets
Reddit database March-June 2017 + YouTube Videos related to the query “Based Stickman” March-June 2017
3. Research Questions
How the Based Stickman’s meme might work as a theoretical prism that can shed multiple lights on different sub-questions?
In particular: how the relation between digital and street activism is articulated in the Alt-Right’s network?
How the Alt-Right re-appropriates tactics traditionally associated with leftist activism?
How the Alt-Right’s fictional aspects might be historically related to other extremist American movements such as the Ku Klux Klan, consequently informing an analysis of the relation between the Alt-Right and its renegaded fascist roots?
Quantitatively , this sub-project relied on Google BigQuery. In particular, we followed three simple steps:
1) Firstly, we collected all Reddit posts that mention “Based Stickman” in the period March-June 2017.
2) Then, we analyzed in which subreddits it compares the most.
3) Finally, we researched which words are most associated with “Based Stickman” on the whole of Reddit over the same period of time.
Then, we visualized these data thanks to RawGraph [fig.1] and WordArt [fig. 2-4].
At the same time, thanks to YouTube Tools, we singled out all the videos related to Based Stickman in the period March-June 2017 organizing them in a tab [Fig. 5: sample]
Such methodology allowed us to research how a casual YouTube video’s snippet becomes first a meme and then an all-around superhero. In other words, how a fictional character emerges in the context of Alt-Right’s peculiar participatory culture. In this sense, qualitatively this sub-project builds on theories of transmedia storytelling and world-building (Jenkins, 2006; Rose, 2011), on philosophical account of fascism (Theweleit) and on historical analysis of the Ku Klux Klan (Gavaler, 2012).
5. Findings + Discussion
This sub-project is still a work in progress; thus, many preliminary findings need to be further studied. However, it’s already possible to scrutinize few outcomes of this research.
1) “We are the ‘Dreamers of the Day’, those who do not want our visions or even our fantasies to be escapes from reality. We want them to be the reality. [...] We demand to live in the world we imagine.” [Richard Spencer3] These words, that white supremacist Richard Spencer pronounced in November 2016, signal a possible trail to follow in order to grasp the zeitgeist of our post-factual age. Indeed, they invite to analyze the cultural milieu that accompanied Trump’s election to the presidency from the point of view of fiction rather than of objective journalism and fact-checking. In this sense, it might be relevant to investigate the American Alt-Right employing frameworks and theories from fiction and fan studies. This somewhat provocative approach implies that -to use the words of David Garcia and Annette Dekker, curators of the exhibition How Much of This is Fiction- “one of today’s most urgent political issues” is “the radical shift in the boundary between fiction and reality in public discourse.”4
It is in this perspective that our understanding of LARPing and cosplaying as political practices need to be framed. As Spencer admonished, these fantasies, rather than being ways to escape reality, leak into reality itself developing a seemingly inseparable mixture. Based Stickman is then an egregious instance of this phenomenon since he represents a collective fantasy that inspires people to action. Moreover, it is worth to be noticed that such intermingling of reality and fiction is a crucial characteristic of contemporary immersive and transmedia storytelling as analyzed by Frank Rose in his The Art of Immersion (2011).
2) Other than being a human meme and an energizing mascot, Based Stickman is at the same time a cosplay, that is a person who dresses up in real life as a fictional character. Impersonating a cosplay can be defined as a kind of “performance art”5. In this regard, the present sub-project confirmed that the notion of performance is significant to understand some peculiarities of Trump’s milieu. Indeed, the term persistently appears in several corners of Trump’s cultural constellation. Firstly, the American tycoon is intimate with the world of wrestling – a relation recently once again emphasized by his retweet of the infamous CNN’s gif6. As known, professional wrestling is officially defined as a performance art, a form of staged spectacle. Then, Alex Jones, founder of the conspiracy media juggernaut Infowars, presented himself as a performance artist during a recent trial7. Thus, the notion of performance seems worth to be further investigated, maybe coupled with that of perception, as two blades of the same metaphorical pair of scissors that cuts the nexus between reality and representation creating a hybrid environment where the two are inextricable8.
3) Another question that this sub-project studies is t he emergence of a fictional character in a context of participatory culture; the fact that in this case the fictional character is a superhero makes the research on his origins even more relevant, given the centrality of origins (the acquisition of superpowers, name and costume) in any superhero tale. Based Stickman emerges rather than is created because there is no single author but a collective and spontaneous contribution of different 4Chan, Reddit and YouTube users.
The database has been fundamental to understand how the narrative was formed and rapidly stabilized. In particular, the analysis of the query “Based Stickman” across the different subreddits allowed to identify (not surprisingly) “The_Donald” as the main place where the identity of the superhero took shape and was linked to real life events. The words most associated with the newborn Alt-Right’s superhero allowed instead to understand how the discussion around him changed over time, from an initial gratitude for his performance at the first “Berkeley Fight” to an increasing ly important focus on his arch-villain (every superhero needs one) that is the perfidious Antifa.
YouTube videos mainly helped to develop a story-line more articulated that the one possible on 4Chan and Reddits. In this regard, YouTube Data Tools granted a clearer idea of how Based Stickman became part of the ever-expanding Alt-Right’s fictional universe. They also highlighted how he received his name: he was just randomly baptized by a YouTube user that called him “stick man” (only later on it became one word) well, because he was carrying a stick and “based” because it’s an Alt-Right positive term that identifies people that dare to be themselves.9
A side a good name, a special weapon or superpower and an arch-villain, a superhero often has sidekicks and allies and Based Stickman is no exception. Since April, he officially10 partners with Gavin McInnes ’ Proud Boys, an association that gathers “white chauvinists that refuse to apologize for creating the modern world” 11. The evident fictional traits of the organization (it also promotes costumes and it has a rule book à la Fight Club) makes it as we will see the right target for the energizing action of Based Stickman.
4) “The streets are dead capital” [Critical Art Ensemble]
As pointed out by Angela Nagle in her Kill All Normies, the Alt-Right has been re-appropriating tactics typical of left-wing activism. Also the practice of dressing up at rallies and demonstrations has so far been eminently associated with progressive movements (think of Gay Pride parades). The Based Stickman’s case also articulates the relationship between digital and street activism, highlighting how they mutually reinforce. In this sense, it sheds a light on discussions typically advanced by the most avant-gardist fringes of progressive activism. I n particular, so-called Tactical Media -a movement that flourished in the final years of the Nineties- addressed the issue of how the “virtual” and the “real” spaces of protest relate, from the bold declaration of the Critical Art Ensemble that at the dawn of the new millennium prematurely announced that the streets were “dead capital” to the more cautious idea of a “hybrid space12” where technological networks and traditional street protests blend, as proposed by Eric Kluitenberg. In this perspective, issues of mapping become clearly central to contemporary activism. It is then significant to notify that organizations such as the Proud Boys re-appropriate this set of issues, as exemplified by the collectively authored map that signals where Antifa members are located [Fig. 6]. The fact that such map is preceded by the question “Have Intel to Share?” adds to it an ironic aftertaste given that the title of the overarching project of which this sub-project is a small part is indeed “Alt-Right Open Intelligence”.
5) One of the main finding that this sub-project has just sketched out and that needs to be substantiated with further research concerns the relationship between the Alt-Right’s media strategy and the aesthetics of other forms of right-wing extremism. In particular, through the Based Stickman’s case, it’s possible to individuate parallels between contemporary American Alt-Right and, on the one hand, the Ku Klux Klan, while, on the other, fascist aesthetics at large. This strand of the sub-project appears particularly relevant since it investigates Alt-Right’s renegade fascist roots; indeed, the discussion developed on Reddit around Based Stickman confirms that people that identify themselves as Alt-Right refuse any assimilation with fascism. At the opposite, they tend to label their adversaries (such as the “Antifa”) with this very accusation; for instance, they call them “nazi”, as showed in the word clouds [fig. 2-3].
However, it’s preliminary possible to argue that there are striking similarities between Based Stickman as an energizing mascot and, for example, other similar fictional characters that galvanized Ku Klux Klan’s actions. In this regard, American scholar Chris Gavaler researched the role that the fictional superhero-like characters named “ the Clansmen” created by author Thomas Dixon for a series of novels had in inspiring real life Klan.13 Along the same lines, scholar Elaine Parsons, author of Ku-Klux: The Birth of the Klan in Reconstruction , has recently argued that the Klan had an “energizing function” building a new “white male identity […] from the newest trends [and] popular entertainment”14; in this sense, Ku Klux Klan’s iconic costumes signaled that the thing the wearer was trying to do was “cultural” not “a political o violent act”. It is quite evident the parallel between Klan members -LARPers ante litteram- and Based Stickman & the Proud Boys both in the way they attempt to build a male identity [fig. 7] and in they way they impose culture as ultimate battleground. In this latter sense, it might be possible to reconnect the present research on LARPing as political practice to a broader discussion on how the American Alt-Right re-appropriated Antonio Gramsci’s notion of cultural hegemony downsizing the emphasis on other aspects of political struggle such as economics.
Ku Klux Klan aside, the cultural milieu that Based Stickman energizes might be rightfully defined “fascist” following the description of the term that German sociologist Klaus Theweleit proposed in his Male Fantasies . What follows is just a first tentative outline of a reflection that would (and hopefully will) benefit of further research. In particular, Theweleit -in his study that primarily builds on novels, letters and memoirs written by Nazis- claims that the kernel of fascism lies in its “fantasy of violence” and that its crucial element is its “explicit sexual language”;15 such fantasy mainly originates in the “fear and hatred of the feminine”. Thus, Theweleit shies away from Marxist and Liberal rationalism taking seriously the irrational component of fascism, its visceral masculinity that exalts “hardness and self-denial”. The male identity proposed by groups such as the Proud Boys and energized by characters such as Based Stickman celebrates the same values, for example highlighting the importance of abstinence from masturbation (see the connection between the “NoFap” community on Reddit and the Proud Boys). Moreover, the focus that the German sociologist puts on the concept of fantasy that precedes actual violence ties his analysis of fascism to the understanding of post-factuality as fictionality that informs this project; to quote white supremacist Richard Spencer once again: “We went them [our visions and fantasies] to be realities”...
6 . Conclusion
To sum up, this sub-project narrated the story of the origins of a fictional superhero that becomes an energizing mascot for some fringes of the Alt-Right. This peculiar “human meme” allowed us to investigate a series of interrelated issues that appear central to grasp the cultural essence of this form of contemporary American right-wing activism.
On a more general level, it confirmed the hypothesis that our post-factual zeitgeist might be rendered as a fictional mediascape. Such approach implies that practices of debunking and objective journalism might not always be the best way to deal with the spread of misinformation that, in our current media vulgata, plagues our Western societies; what’s indeed the point of fact-checking a fictional story?
More in specific, the Based Stickman’s case is significant on multiple levels: it shows how a fictional narrative is created in a context of political participatory culture, it demonstrates once again that the Alt-Right is re-appropriating tactics traditionally associated with progressive activists and, above all, it proposes ways to tie the Alt-Right to the Ku Klux Klan’s and more in general fascist’s aesthetics, reaffirming the centrality of culture as political site.
7 . References
Costanza-Chock, Sasha  Out of the Shadows, Into the Streets!: Transmedia Organizing and the Immigrant Rights Movement, Cambridge MA: MIT Press
Gavaler, Chris The Ku Klux Klan and the birth of the superheroin Journal of Graphic Novels and Comic, Routledge
Jenkins, Henry  Convergence Culture: Where Old and New Media Collide, New York, New York University Press
Kluitenberg, Eric  Legacies of Tactical Media, Amsterdam, Institute of Network Cultures
Nagle, Angela  Kill All Normies: Online Culture Wars From 4Chan and Tumblr to Trump and the Alt-Right, Zero Books
Rose, Frank  The Art of Immersion: How the Digital Generation is Remaking Hollywood, Madison Avenue and the Way We Tell Stories, New York, London, W.W. Norton & Company
Theweleit, Klaus  Male Fantasies, Vol.1 & 2, Minneapolis, University of Minnesota Press
Klaus Theweleit, Male Fantasies Vol, 1 & 2,
University of Minnesota Press, 1987
The Alt-Right as (mis)readers of ‘Cultural Marxism’
Summary of Key Findings
In the course of the two weeks at the Digital Methods summer school, 2017, this subproject was developed as part of the Alt-Right Open Intelligence Initiative, to understand the Alt right’s imaginary and their representation of the Frankfurt School’s thought. The initial interest in this particular topic was sparked by a number of references to Cultural Marxism in some of the alt right discussion forums as observed by Marc Tuters. A key finding of this subproject was that the alt right and their representation of Cultural Marxism through memes, images, videos is not a new phenomenon but in fact is very much in continuation with the new Right movement that began in the 90s. This was established over the course of two week with the contention that with the alt right’s hijacking of multiple spaces on the web, only the form in which their ideas are disseminated has changed. In line with the overarching project, it is observed how the alt right has co-opted many of the issues and even discourses that were previously associated with the left. The alt right’s discursive strategies in discussing Cultural Marxism seem to be following a similar agenda, of a cultural war deploying semiotic guerilla tactics (Eco, 1983)
Eco (1983) argues that in a chain of communication, there is a source that transmits the message, via a signal emitted through a channel and there is a receiver. But there is a fundamental requirement of a Code, which clearly transmits information without any disturbances such as noise. Another important thing to note here is that the code is shared both by the sender and the receiver. But also, a code is already established system of probabilities on the basis of which we can decide whether the elements of a message are intentional. Any message can thus be encoded with a different semantic meaning. For Eco (1983) in so far as the receiver transforms the signal transmitted into a message, communication is working but the message in itself is still empty of any meaning to which the sender can attribute different meanings depending on the Code that is applied to it. So for instance, repeatedly, “cultural Marxism” is associated with political correctness in Alt right discussions (in both the New Right Manifestos such as Andrew Breitbart’s Righteous Indignation to 4chan /pol/).
Moreover, he argues that while in everyday life, the Code is fairly established in advance so that the meaning is established, in aesthetic communication, often this Code is deliberately made ambiguous so that the receiver can ascribe multiple meanings to it. In the case of the Alt right, “pepe the frog” is a form of a code that is still an empty message that finds its completion in the chain of communication only when the receiver decodes the message as the sender intended it to be. Similarly, the alt right’s reading and subsequent coding of the imagery related to cultural Marxism seems to be deploying the same tactic. By intentionally imbuing symbols/signs previously associated with the left (for instance, the red pill, or the semantic meaning of free speech), the alt right changes the meaning of these signs thus changing their signification. But at the same time, the signifiers that earlier had positive connotations are turned negative, such as feminists or SJWs, or Critical Theory.
It is deemed necessary for those of us in the Humanities to be aware of this ‘spectre that is haunting the internet’- the Alt right and for good reason. The ideological underpinnings of the alt right are often discussed and what is interesting to find is the mention and discussion of many theoretical ideas most commonly those associated with the Frankfurt school, clubbed under the umbrella term of Cultural Marxism on many of the online platforms such as 4chan, Reddit, Google, Wikipedia, or even YouTube
. The initial research questions posed by Marc Tuters suggested, that there was a need to analyze and understand how the Alt right reads ideas of the Frankfurt school. After the first week of initial research and reading of various online comment threads on 4chan and reddit, it was decided that a closer reading of the discourse of the alt right and the alt light (not specifically either) on their discussion of Cultural Marxism and at the same time an analysis of the imagery shared on various web platforms such as 4chan.org/pol/ and reddit.com threads was necessary to make any further claims. For this purpose, a discourse analysis and a semiotic analysis approach was utilized with a specific focus on both images scraped from reddit.com that contained the word ‘cultural Marxism’ in their comments.
2. Initial Data Sets
The initial data sets available at the beginning of the DMI summer school, 2017, included the following:
- Reddit Big Query
- 8M 4chan/pol/ posts from 2 ½ months starting June 30th 2016
- 4chan/pol/ & 8chan/pol/ collected from June 1 2017
- Preliminary look at pages such as Smash Cultural Marxism, Identity Evropa, Breitbart.com, Radixjournal.com
3. Research Questions
The initial research questions as stated in the project descriptions were:
- How does the alt-right read critical theory that which they amalgamate under the term ‘cultural Marxism’? What role does the Frankfurt School’s thought play in the alt-right’s imaginary?
- Is there a relationship between memes that circulate in alt right circles on the web on Cultural Marxism and anti-semitism—and the ((())) memes?
With the first week of initial research on the topic, it was decided to include a few research questions relevant to the available reddit datasets. These were:
- What is the imagery associated with the term “cultural Marxism” as discussed on various subreddits? Does the imagery tell us something about the nature of the discourse of the alt right on cultural Marxism? How do the associated comments help in making sense of this discourse?
During the first week of the Summer School, with the initial insights from the Extremism Analysis Unit, we decided to first find out how often the concept of “cultural Marxism” gets discussed in certain online forums. This initial part of the sub-project relied on Google BigQuery
. In particular, we followed three simple steps:
1) Firstly, we collected all Reddit posts that mention“cultural Marxism” from the
period 2007- May 2017.
2) Then, we analysed in which subreddits it appears the most.
3) Finally, we researched which words are most associated with“cultural Marxism” on the whole of Reddit over the same period of time.
Then, we visualized this data using to RawGraph
[fig.1] and WordArt
[fig. 2-] for different time periods. Figure 1 here is a graph of the reddit data between the years 2014-2017.
Figure 2 is a word art visualisation for the month of October, 2016. The reason for selecting this month was related to the increased activity of Trump fans on reddit during his election campaigns. As this was already an observation made in another subproject in the Alt Right Open Intelligence Initiative project, we selected this month to check if the phrase “cultural Marxism” was discussed often as well during this time period.
Figure 1 Raw Graph
Figure 2 Word art October, 2016
During the second week, as the focus was to be able to analyze the imagery associated with the term “cultural Marxism”, an image bank was created using the reddit dataset. (From Recipe #4) As it happens on reddit, images are shared as part of the comments and are stringed to the text, as users often link images into the comments. Downloading images along with the comments proves to be exceptionally useful while attempting a discourse analysis as it provides the researcher with not just an image but the con(text) or discussion around the shared image as well. A tool was created to extract the comments containing links to images as a .csv file. For this particular subproject, an Image Explorer tool was created by searching the whole of reddit for the use of keyword “cultural Marxism”.
Further, once this data set was extracted, using ImageJ
and a visualization all of the image data set was created. ImageSorter
proved to be a very useful tool as a faster way to categorize and organize the large image dataset into different genres. ImageSorter
automatically sorted out images that were repeated, black and white images, diagrammatic images into different groups in a single visualization.
Alongside the reddit big query dataset, for a closer discourse analysis a number of secondary sources were also used including various new right manifestos, important documents on the web.
The analyzed manifestos are listed as follows:
- Micheal Mimicinno’s New Dark Age: Frankfurt School and ‘Political Correctness’ (1992)
- William Lind’s The Origin’s of Political Correctness (2000)
- Pat Buchanan’s Death of the West (2001)
- Andrew Breitbart’s Righteous Indignation (2011)
- Andres Breivik’s Manifesto A European Declaration of Independence (2011)
- Vincent Law’s Radix Journal article titled Marcuse’s Blue Pill (2014)
Based on the two available datasets, the methodology/approach was that of a multimodal discourse analysis as theorized by Gunther Kress and Theo van Leeuwen (2001). For the purpose of this subproject we restricted the analysis to include a
- Textual Discourse Analysis (that of the reddit comments and the various manifestos) and;
- A Visual Discourse Analysis (that of the images scraped from the reddit comments containing the word “cultural Marxism”.
Kress and van Leeuwen (2001) rightly argue that the dominance of monomodality in the field of semiotics needs to be thought over. There is a need for visual semiotics to consider the multimodality of digital objects (such as images), to include the different modes of representation that allow for a ‘framing’ of the visual content. In the case of this project, we found it useful to look at the images associated with comments that included the keywords “cultural Marxism” to provide us with a particular context in which these images were shared. As opposed to a simple google image search, it allowed for a more in depth view of the representation of “cultural Marxism” in form of images, but also the discursive strategies used by the alt right to supplement this representation.
Textual Discourse Analysis
As stated above in the Methods section, a data set of the most co-occurring words along with ‘cultural marxism’ on reddit was created. Discourse analysis is an analysis of the patterns that people’s utterances follow when they participate in conversations on an everyday basis. The initial method used in Week 1 was to explore an abstract mapping of the discourse on cultural Marxism on reddit. One can understand this as an attempted exploration of the discursive struggles (Laclau and Mouffe) as a way for the alt right to achieve hegemony to alter the semantics of the way cultural Marxism is understood or discussed.
Laclau and Mouffe (1985) in their discourse theory offer an understanding of how the social is constructed through a discourse. They ground this theory in the idea that meanings of signs is never fixed and is always open to constant struggles. Although there is an attempt to arrive at some sense of fixity of signs in their relation to other signs to make communication possible, discourse analysis then aims to offer a map of these struggles to understand how a certain meaning came to be normalized and gain a hegemonic status. In using this theory here, our attempt is to flesh out a mapping of the discursive strategies used by the alt right to establish a sense of fixity to signs in relation to other signs in an attempt to normalize those meanings. Here the aim is to single out the alt right’s discourse on “cultural Marxism”. Just as Laclau and Mouffe (1985) argue this can be done by the exclusion of the other meanings that are also possible. As it is observed later in the section on analysis, there are contestations on the discussions on this topic on various subreddits, the idea is to exclude these contestations to specifically be able to identify the alt right’s discursive strategy, or their field of discursivity
(Laclau and Mouffe, 1985, p 111). As a concrete method, discourse theory aims to focus on how specific articulations establish certain meanings in particular relations with one another. It is crucial to point out how political becomes a central concern for Laclau and Mouffe as a focus of analysis. What becomes naturalized is the outcome of political discursive struggles and becomes a part of overall consensus. For instance, one can see how the ideas around “PC culture” in the language of the Alt right and its associated negative connotation is becoming more naturalized now in everyday vernacular of the youth.
Certain conceptual tools used for such an analysis are:
- Nodal points- A nodal point can be defined as a sign that us privileged and in relation to which the other signs are organized or gain their meaning. (Jorgensen & Phillips, 2011, p. 4)
- Hegemony and discursive struggles: For Laclau and Mouffe (1985), it is through a successful hegemonic intervention that one discourse dominates another in the discursive field by a rearticulation of its elements.
Empirically, by scraping the data on co-occurrence of words with cultural Marxism on reddit, one could explore these words and the frequency with which certain words were used and how this changed over time. Along with this, by delineating the data to get the names of the subreddits where the phrase ‘cultural marxism’ was used most, some important preliminary findings were made. So here, the intertextuality (Fairclough, 1995) of the discourse can be explored, by analyzing not just the words most commonly used but also taking into account as to ‘where’ this phrase appears the most and what meanings it aims to stabilize.
Visual Discourse Analysis
As stated above in the section on Methods, one of the key aims of this subproject was to analyze the Imaginary of cultural Marxism for the Alt right. For this purpose, exploring a pattern in the visual discursive formation was deemed crucial. As mentioned, ImageSorter
categorized the different patterns of images shared into different groups in the visualization.
This grouping of images allowed us to view the images that were obviously repeatedly used on various subreddits. Once this pattern was visualized, it became easier to code them into the following genres:
- Black and white images (historical references to events/people)
- Diagrammatic images (Alt right’s creation of various diagrams creating associations between cultural Marxism and other ideas such as ‘political correctness’, Jews, Feminism, SJWs and so on, also includes maps)
- And Other (miscellaneous images shared in context with particular discussions)
Once this coding was complete, ImageExplorer
was used to look at the most repeated images, and the specific genres of images for a closer reading within the context of the comments and discussions linked to them. The images made much more sense with the accompanying comments as it gave us an insight into how the users on reddit engaged with these images.
- A part of the aim was also to integrate and find some coherence and possible links between the list of words extracted in Week 1 from the reddit dataset and the key (most repeatedly occurring) images. Is there a possibility of a meaningful reading of these clusters of words and images?
Gillian Rose makes a crucial point in understanding the framework of a particular discourse. She argues that an important aspect of discourse analysis is how does a particular discourse attempt to ‘produce its effects of truth’? (Rose, 2007, p. 161) How does the discourse of the Alt right on cultural Marxism, attempt to produce certain claims of truth about the nature of ideas of Frankfurt school?
Describe your findings. Consider any counter-intuitive findings.
Textual Discourse Analysis Findings:
Interestingly, in Week 1, as Figure 1 shows, the term Cultural Marxism got mentioned the most over the time period between 2014-2017, in subreddit /thedonald/. Although there are subreddits that do not necessarily accommodate Alt right discussions for instance, /Marxism/ or /fullcommunism/, this term has been relatively discussed way more often in the /Donald/ which is an established Alt right subreddit. This was an interesting preliminary insight for us.
Similarly, Figure 2 shows the associated words most commonly used with cultural Marxism for the month of October, 2016. This month was specifically selected as per the findings from other simultaneous projects suggested that this was a month of high activity amongst Trump fans on reddit and the Trump Election campaign. Since the data set of words that we scraped had hundreds of words, we decided to restrict the data to the 15 most co-occurring words. It is to be noted that the words selected are using a selection that avoids the most generic words that appear the most as they may alter the reading of the data. For instance, one such words that appears the most in Figure 3 is ‘term’, which does not provide us with any additional information about a discourse.
The fifteen most predominantly used words (in Figure 2) here are:
White, Theory, Social, Culture, Race, Men, Women, Rights, Feminism, Conspiracy, Political, Frankfurt, Ideology, Marx and Jews.
This process was repeated for four different months in 2016 and 2017 to find out the co-occurrence of words and how it changes.
Figure 3 Word art, Jan 2015
15 Most commonly used words:
Conspiracy, theory, gg, gamergate, article, feminism, SJWs, Jews, pill, ideology, Marxists, Breivik, media, race, critical
Figure 4 March, 2016
15 most commonly used words:
White, political, correctness, conspiracy, theory, term, American, race, Lind, conservative, att, speech, west, media, Frankfurt
Figure 5 April, 2017
15 most commonly used words:
Frankfurt, school, Marxists, parrot, Islam, conspiracy, Nazi, values, speech, freedom, identity, media, industry, Jews, America, western
If we deduce from a superficial reading of all these words into a cluster of ten most recurring words, they’re enlisted here:
White, Marxists, feminism, conspiracy, theory, Jews, media, ideology, race, America
What is also interesting is the mention of words that appear only in some months. For instance, gg and gamergate in Jan 2015. This tells us that the term cultural Marxism was also discussed in relation to gamergate in this month. In the same month there is also a use of terms that do not often appear in other data sets. Terms such as Breivik, SJWs and pill. Similarly in the month of April, 2017, words such as Lind (Bill Lind), Islam and Nazis start to appear. What can be incurred from these word associations is a preliminary narrative of the discourse.
Discourse Analysis of the enlisted Alt Right Manifestos
A discourse analysis of the enlisted manifestos was then undertaken to find out how related/similar is the narrative of the 90s new right and the alt right (considering that they mention both Bill Lind and Andres Breivik). Some brief excerpts from Andres Breivik’s 2083- A European Declaration of Independence
(2001) tells us how the first topic that he discusses is titled The rise of cultural Marxism/multiculturalism in Europe
. Wherein he goes on to describe in great detail ‘political correctness=cultural Marxism=multiculturalism’. He states,
Just what is “Political Correctness?” Political Correctness is in fact cultural Marxism (Cultural Communism) – Marxism translated from economic into cultural terms. The effort to translate Marxism from economics into culture did not begin with the student rebellion of the 1960s. It goes back at least to the 1920s and the writings of the Italian Communist Antonio Gramsci. In 1923, in Germany, a group of Marxists founded an institute devoted to making the transition, the Institute of Social Research (later known as the Frankfurt School). One of its founders, George Lukacs, stated its purpose as answering the question, “Who shall save us from Western Civilisation?” The lineage is clear, and it is traceable right back to Karl Marx.
This is the first major parallel between classical and cultural Marxism: both are totalitarian ideologies. The totalitarian nature of Political Correctness can be seen on campuses where “PC” has taken over the college: freedom of speech, of the press, and even of thought are all eliminated. Cultural Marxism defines all minorities, what they see as the victims; Muslims, Feminist women, homosexuals and some additional minority groups as virtuous and they view ethnic Christian European men as evil.
Marcuse may be the most important member of the Frankfurt School in terms of the origins of Political Correctness, because he was the critical link to the counterculture of the 1960s
As another example, one can note the similarities between the discussions in William Lind’s Origins of Political Correctness (2000)
. He states:
What is political correctness? If we look at it analytically, if we look at it historically, we quickly find out exactly what it is. Political Correctness is cultural Marxism. It is Marxism translated from economic into cultural terms. It is an effort that goes back not to the 1960s and the hippies and the peace movement, but back to World War I. If we compare the basic tenets of Political Correctness with classical Marxism the parallels are very obvious.
First of all, both are totalitarian ideologies. The totalitarian nature of Political Correctness is revealed nowhere more clearly than on college campuses, many of which at this point are small ivy covered North Koreas, where the student or faculty member who dares to cross any of the lines set up by the gender feminist or the homosexual-rights activists, or the local black or Hispanic group, or any of the other sainted “victims” groups that PC revolves around, quickly find themselves in judicial trouble. Within the small legal system of the college, they face formal charges – some star-chamber proceeding – and punishment. That is a little look into the future that Political Correctness intends for the nation as a whole.
Just as in classical economic Marxism certain groups, i.e. workers and peasants, are a priori good, and other groups, i.e., the bourgeoisie and capital owners, are evil. In the cultural Marxism of Political Correctness certain groups are good – feminist women, (only feminist women, non-feminist women are deemed not to exist) blacks, Hispanics, homosexuals. These groups are determined to be “victims,” and therefore automatically good regardless of what any of them do. Similarly, white males are determined automatically to be evil, thereby becoming the equivalent of the bourgeoisie in economic Marxism. And particularly Marcuse, who in his own writings calls for a society of “polymorphous perversity,” that is his definition of the future of the world that they want to create. Marcuse in particular by the 1930s is writing some very extreme stuff on the need for sexual liberation, but this runs through the whole Institute.
Visual and Textual Discourse Analysis Findings:
A visual discourse analysis of the visualization of images from reddit showed a similar narrative. Although there are different subreddits where the same images are shared but albeit with a counter-argument, as an attempt to argue against the claims made by those users quoting alt right sources. We thought it to be prudent to list out a few of such counter-narratives as well so as to make it clear that this is not the only narrative of cultural Marxism on reddit.com. There is a sense of an ongoing struggle within online communities in trying to respond to such discourses. An important part of a discourse analysis method is to understand whether a discourse is actually a dominant discourse. In case of this sub project, further research needs to be conducted in order to determine whether the alt right’s discourse, is actually the dominant discourse. But what substantiates the claims being made here is the coinciding of a narrative across different media (the New Right manifestos, word associations, images, YouTube
As mentioned above, the most recurring images were viewed for a closer reading using ImageExplorer
tool. Images such as these as an exemplar are shared the most number of times as it appears on ImageSorter
. We have also here posted the comment threads where these images were shared on reddit.
Figure 6 Andres Breivik's house in Oslo
Figure 7 A photo of Andres Breivik
Today you get to learn something youngin. http://imgur.com/a/KqZUt http://imgur.com/a/0xFEo
The truth about immigration, by the numbers: >https://www.youtube.com/watch?v=LPjzfGChGlE [Embed] Cultural Marxist Jews Admit Organizing White Genocide The plan to eliminate the white race: >https://www.youtube.com/watch?v=bOgkGzMdieI [Embed] Cultural Marxism in action� Political Correctness, the tip of the blade: >https://www.youtube.com/watch?v=q6c_dinY3fM [Embed] Cultural Marxism & Social Justice Explained: >https://www.youtube.com/watch?v=xnqIj8C2Aek [Embed] Why are we in Decline - Cultural Marxism: >https://www.youtube.com/watch?v=VggFao85vTs [Embed] also see The facts about slavery in North America: >https://www.youtube.com/watch?v=b5tci36bNjg [Embed] Cultural Marxist Jews fund media propaganda against whites on an enormous scale: >https://www.youtube.com/watch?v=-4Ojbi6lXQI [Embed] Does this sound familiar at all? (starting at 6:52) >https://youtu.be/kPdxhLUKZYM?list=PLo0ThsDnveH5nv5TNviBrGTX9P6IrYfIe&t=412 [Embed] The Holocaust: >https://www.youtube.com/watch?v=tPc899uUb-A [Embed] >https://www.youtube.com/watch?v=jgGP_evkvOk [Embed] >https://www.youtube.com/watch?v=TxpIsep4160 [Embed] Welcome, to the real world.
Figure 9 An image fro subreddit: /r/PublicHealthWatch
Take a quick look at who rules all the world banks, federal reserve, media including hollywood etc, big pharma, printing press, the same creatures who's subversive values are deeply rooted in [communism](
), parasitism and [cultural marxism](https://i.imgur.com/R73gcMr.jpg)(frankfurt
school) especially since after WW2. Through a long process they've gained enough power and now they want to degenerate, uproot, destabilize society to the point where a potential uprising against their power will be impossible. For example; The [Who owns the media?](
) Reddit is no different, owned by certain tribesman Samuel Newhouse. [This video explains a little bit how the successful process gained traction in recent day America](https://www.youtube.com/watch?v=qlpODYhnPEo
Figure 10,10 and 11 Diagrammatic style images
Figure 11 Map style Image from subreddit /r/hoi4
Again, to be clear, these aren't in the tenants of marxism, no. However, cultural marxism
is pretty much exactly as described by the urban dictionary definition-literally a commie plot to destabilize the US. The USSR is long dead but the poison dart is just kicking in, in the form of a destabilized and I dare say degenerate US. I don't know how they did it, specifically (I really want to know TBH, the knowledge of how to doom a country to a cultural decline and collapse is more powerful than even nukes!) The same thing has affected europe, but they are much farther along than us.
For example if you've been paying attention, you'll know that germany's current leader is Angela Merkel, a woman who has imported millions of violent refugees with no screening process whatsoever, banned gun ownership, and begun literally jailing people for wrongthink, all while ignoring her plummeting approval rates. 1984
Figure 12 Meme style image
Figure 8 A photograph of Adorno's confrontation witb feminists
(This is an example of the counter narrative on the discussion, trying to point out the flaws in the alt right narrative of cultural Marxism)
/u/commiespaceinvader has an excellent [write-up](https://www.reddit.com/r/AskHistorians/comments/4ivbfo/were_the_original_members_of_the_frankfurt_school/
) on the absurdity of Cultural Marxism as an idea, my answer will try (imperfectly) to address the origins of this idiocy. >I still don't know what "cultural Marxism" means. This is actually not something to be ashamed of, because there is no firm definition of CM by its adherents. It is an abstract slur that has nothing to do with the actual philosophy of the Frankfurt School or its ideas. The generalized picture of CM according to sites like Reddit or Youtube is that Cultural Marxists are a bunch of sex- and identity politics-obsessed intellectuals who despise (white) Western civilization and are trying to pull it down from the inside. CM found common cause, or were indistinguishable, from the New Left and form the basis for an intellectual conspiracy. As the OP's reading into the Frankfurt School's work suggests, such an interpretation is absurd. To give an example of this, Adorno was notoriously conservative and straight-laced, much to the chagrin of the increasingly radical student body of the University of Frankfurt. In April 1969, the students demanded in his lecture that he engage in self-criticism and disrupted the professor. Some of this disruption involved walking up to the chalkboard and writing anti-Adorno statements, but most famously, a group of female students [took off their tops](
) (obviously NSFW) and [accosted the old man](
). This type of disruption shocked Adorno and he called the police. In a letter to Marcuse, Adorno wrote: >The police should not be�to use the jargon of the ApO
�abstractly demonized. I can only reiterate that they treated the students far more leniently than the students treated me: that simply beggared description. I disagree with you on the question of when the police should be called. Recently, in a faculty discussion, Mr. Cohn-Bendit told me that I only had the right to call the police if blows were about to rain down on me; I replied that, by then, it would probably be too late. The Busenaktion
(breast action/operation) shows that notions of a united intellectuals front between 60s radicals is often overblown, but also the 60s intellectual milieu was often characterized by fratricidal conflicts that would make any common conspiracy to overthrow the West, even if it did exist, a most complicated proposition. The intellectual genesis of CM, like many conspiracy theories, is difficult to track down as it had many different origin points. The American Paleoconservatives Pat Buchanan and William S. Lind certainly helped popularize the idea of a common conspiracy among academic intellectuals against the West. Their writings picked up cosmetic elements of the Frankfurt School and twisted them all out of proportion. In a typical passage in Buchanan's The Death of the West
, he writes: >Cultural Marxists understood [the power of the politics of personal destruction]. Their Critical Theory was a prototype of the politics of personal destruction. What the latter does to popular leaders, Critical Theory does to an entire nation through repeated assaults on its past. It is the moral equivalent of vandalizing the graves and desecrating the corpses of its ancestors. > Many of the institutions that no have custody of America's past operate on the principles of Big Brother's Ministry of Truth: drop down the "memory hole" the patriotic stories of America's greatness and glory, an produce new "wart-and-all" histories that play p her crimes and sins, revealing what we have loved to be loathsome and those we have revered to be disreputable, even despicable. Many old heroes have not survived the killing fields of the New History. Buchanan's screed here conflates multiple intellectual traditions and disciplines into a single, undifferentiated mass that operates on the same plane as Pol Pot (killing fields). The Decline of the West
draws on anti-intellectualism and a long-developed distrust of the academy in certain conservative circles, presupposing an near-monolithic control of these institutions by critical theory. Likewise, William Lind argued that CM was behind the emergence of political correctness and stifling intellectual "debate" by preventing alternative viewpoints on campus. Again, neither Lind nor Buchanan bother to understand the ideas of the Frankfurt School or the precepts of critical theory, all that matters is to describe it as the enemy. Buchanan and company also had the benefit of widespread narratives of communist subversion and cabals that had been developed in milieus like the John Birch Society. One of the consistent minor themes in the Cold War discourse is that social movements like the African-American Civil Rights movement were infiltrated by CPUSA agents and they were the ones pushing expressions of discontent. The Marxist moniker in CM itself conjures up images of would-be vanguardists in the academy plotting to further the cause of revolution; The Death of the West
likens Adorno, Marcuse, and other critical theorists to Marxist revolutionaries of prior generations. And as with other fringe theories on Marxist subversion, proponents of CM dabble in antisemitism. William Lind [spoke at a Holocaust denial conference in 2002](https://www.splcenter.org/fighting-hate/intelligence-report/2002/ally-christian-right-heavyweight-paul-weyrich-addresses-holocaust-denial-conference
) and Buchanan has periodically attacked the importance of Israel to US foreign policy and in news columns in the 1980s argued that Nazi war criminals were victims of KGB frame-ups. While not blaming Jews directly, Buchanan employs a variety of dogwhistles implying a unified Jewish conspiracy to advance its agenda. In a similar vein, in a 2000 speech [The Origins of Political Correctness](http://www.academia.org/the-origins-of-political-correctness/
), Lind summons up images of nefarious Jews: >How does all of this stuff flood in here? How does it flood into our universities, and indeed into our lives today? The members of the Frankfurt School are Marxist, they are also, to a man, Jewish. In 1933 the Nazis came to power in Germany, and not surprisingly they shut down the Institute for Social Research. And its members fled. Of course, this all begs comparison to the Nazi's own propaganda use of "Cultural Bolshevism" to slander political opinions and individuals as tools of international Jewish Communism. Like adherents of the CM conspiracy today, the Third Reich used the term loosely without any real definition of what it meant. The idea of an intellectual conspiracy to undermine the West is of course nonsense. As /u/commisespaceinvader notes the Frankfurt School had a diverse set of beliefs and were far from a united front. But this reality is immaterial to the importance of Cultural Marxism as a slur. The preexisting set of conspiracies and ideas developed by the likes of Lind gives this slander a degree of flexibility, especially for people who cannot even be bothered to understand what the Frankfurt School actually wrote.
The first two images Figure 6 and 7 are Andres Breivik’s house in Oslo and his image next to it. The text accompanying these two images
An example of the comments associated with the images on subreddit- /r/conspiracy.
The narrative here can be discerned along with the previously noted word associations and a transcription of the YouTube videos (as stated above).
- It was observed how the alt right makes a clear association between political correctness and cultural Marxism.
- What we find here in the analysis is this discursive struggle waged by the alt right, to establish an understanding of certain ideas, signs and symbols that have been previously associated with the political left, with the aim to subvert their meanings. Terms such as “freedom of speech”, “feminism”, “minority groups”, all attain a negative connotation in their field of discursivity.
- A certain narrative is constructed around specific theoretical ideas. Most commonly, Herbert Marcuse’s ideas are often discussed. There is often a way of constructing a narrative by decontextualized quoting from the texts. Marcuse’s ideas in Eros and Civilization are reduced to this term “polymorphous perversity” as associated with the sexual liberation movement of the sixties but without any reference or a discussion of the pleasure principle, reality principle and their relevance to culture in capitalist societies. The notion of a critique of capitalism, which was one of the central tenants of the Frankfurt school is almost never mentioned.
- It is repeatedly mentioned in these texts that these were Jews escaping Nazi Germany (which is true) but following an explanation that they wanted to destroy American society and their values. This was also found repeated in the YouTube videos transcribed (linked on Alt right pages such as Smash Cultural Marxism and Identity Evropa)
- Often, the history of the Frankfurt school is described more rigorously than any of their actual theoretical ideas. For instance, many of the manifestos elaborate on the Jewish origins of the theorists. For instance, in his online manifesto titled Frankfurt School and the Origins of Political Correctness, Michael Mimmicino (a self-proclaimed paleoconservativist) states, “The task of the Frankfurt School, then, was first, to undermine the Judeo-Christian legacy through an "abolition of culture" (Aufhebung der Kultur in Lukacs' German); and, second, to determine new cultural forms which would increase the alienation of the population, thus creating a new barbarism." As can be seen, a common discursive strategy used here is quoting words completely out of their original context, to serve an ideological purpose. As if Lukacs’ critique was not rooted in a critique of capitalism or a critique of what resulted into two world wars and the alienation caused by capitalism.
- It is also to be noted that a number of threads suggest an attempt to disassociate Marx and the Frankfurt school ideas, holding Marx’s notion of a class struggle as something to be admired but at the same time denouncing the Cultural Marxists for devaluing base over superstructure. This is done by quoting Adorno, Lukacs’, Marcuse often, decontextualized from their actual arguments, as if they were never Marxists in the first place. It is to be noted that there is a danger in assuming that there is no serious discussion, thought given to the theory itself but online discussions automatically assume the nature of being a bad/superficial reading of the theories being discussed. One would be surprised to the seriousness with which a lot of the texts are read and discussed on these forums. This was established using a detailed discourse anlaysis of comment threads, related to images containing the term Cultural Marxism shared on reddit.com.
- There are also references made to all progressive ideas as originating from this school of thought with the use of diagrams and maps. Instances of associating all progressive movements such as the feminist movement, black civil rights movements, gender debates and so on to be originating from this one umbrella term cultural Marxism, but also changing the connotations associated with them. So turning feminists into feminazis, SJWs libtards and so on.
- So going back to Laclau and Mouffe’s discourse theory, we suggest here that “political correctness” is the nodal point around which the discursive field of the alt right on “cultural Marxism” is constructed. It is this nodal point in relation to which all the other related signifiers find a negative connotation, such as feminism, liberals, SJWs and so on.
Discuss and interpret the implications of your findings and make recommendations for future research and application, be it societal, academic or technical (or some combination).
List your references in a standard academic bibliographic format.
List of online articles:
List of YouTube
Jorgensen, M., & Phillips, L. J. (2011). Laclau and Mouffe's Discourse Theory. In M. Jorgensen, & L. J. Phillips, Discourse Analysis as Theory and Method
(pp. 24-59). London: Sage.
Laclau, E., & Mouffe, C. (2001). Hegemony and Socialist Strategy.
London, New York: Verso.
Nagle, A. (2017). Kill All Normies: Online culture wars from 4chan and Tumblr to Trump and the alt-right.
Rose, G. (2007). Visual Methodologies- An Introduction to the Interpretation of Visual Materials .
London, New Delhi, California: Sage Publications.