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.
Youtube analysis
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 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.
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.
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.
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.
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.
The alt-right, we also noted, takes advantage particularly of events. Its ‘use’ of events may be highlighted by the Berkeley case.
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.
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.
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.
| 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 |
What are the dominant issues on 4chan /pol/?
What Wikipedia articles does 4chan /pol/ refer to?
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:
War
History
48 articles containing ‘empire’
Geography/countries
Religion
532 articles containing ‘list of’
Also, many articles seem fairly obscure or out-of-place at first sight. A quick sample provides titles such as:
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.
< 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.
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.
| SELECT |
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() |
Next, we used a word association script:
| SELECT a.word, b.word, c, ratio |
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 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: Mythology 87% Pc Game 70% Religion 65% Computer Wallpaper 64% Warlord 55% Cg Artwork 53% | Web detection results: Donald Trump 15.4942 Vladimir Putin 7.0778 Warhammer 40,000 Crippled America 1.0738 Donald Trump presidential campai... 0.52606 Meme 0.41857 God 0.40899 Image 0.35087 4chan 0.34832 Armour 0.28115 Imperium 0.27839 Heresy 0.25355 Imgur 0.24643 Crying 0.24382 Gender 0.23817 |
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.
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.
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.| Google Vision | Manual Annotation | Intersection of manual and auto positives | |
| Positive marks | 338 | 545 | 564 |
| Negative marks | 8,444 | 8,238 | 8,219 |
| False positives (compared to manual) | 74 | N/A | N/A |
| False negatives (compared to each other) | 226 | 19 | N/A |
| Percentage of actual entities (compared to each other) | 52.98% | 96.63% | N/A |
| Reliability of positive marks (compared to manual) | 78.11% | N/A | N/A |
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.| Positive marks | 36 |
| Negative marks | 970 |
| False positives (manually checked) | 7 |
| False negatives (manually checked) | 34 |
| Percentage of actual entities (considering false negatives) | 51.43% |
| Reliability of positive marks (considering false positives) | 80.56% |
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.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.
Reddit database March-June 2017 + YouTube Videos related to the query “Based Stickman” March-June 2017
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?



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). 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”...

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.
Costanza-Chock, Sasha [2014] Out of the Shadows, Into the Streets!: Transmedia Organizing and the Immigrant Rights Movement, Cambridge MA: MIT Press
Gavaler, Chris [2012]The Ku Klux Klan and the birth of the superheroin Journal of Graphic Novels and Comic, Routledge
Jenkins, Henry [2006] Convergence Culture: Where Old and New Media Collide, New York, New York University Press
Kluitenberg, Eric [2011] Legacies of Tactical Media, Amsterdam, Institute of Network Cultures
Nagle, Angela [2017] Kill All Normies: Online Culture Wars From 4Chan and Tumblr to Trump and the Alt-Right, Zero Books
Rose, Frank [2011] 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 [1987] Male Fantasies, Vol.1 & 2, Minneapolis, University of Minnesota Press
1https://www.washingtonpost.com/news/post-nation/wp/2017/03/05/pro-trump-rally-in-berkeley-turns-violent-as-protesters-clash-with-the-presidents-supporters/?utm_term=.d0c69d101af6
14See Malcom Harris, Lol Klans, Pacific Standard, June 2017 [https://psmag.com/social-justice/the-ku-klux-klan-were-memelords]
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.
2017-04-02 14:55:14
Subreddit: MGTOW
Score: 41
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)
2016-05-31 21:23:08
Subreddit: PublicHealthWatch
Score: 2
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
2016-08-07 07:36:34
Subreddit: hoi4
Score: -1
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.
2016-12-05 17:18:30
Subreddit: AskHistorians
Score: 253
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.
Copyright © by the contributing authors. All material on this collaboration platform is the property of the contributing authors.