The economy of culture is, accordingly, not a description of culture as a representation of certain extra-cultural economic constraints. Rather, it is an attempt to grasp the logic of cultural development itself as an economic logic of the revaluation of values.
I am enjoying Groys’ non-market ‘economic’ interpretation of Nietzschean truth. He develops an economic conception of Nietzsche’s non-moral version of value without turning to Marxist conceptions of value that would position cultural value as a consequence of the social relation between capital and labour power.
In my True Detective essay I develop a notion of ‘meta’ so as to grapple with the epistemological displacement that occurs in the midst of a revaluation of values. I call this a ‘liminal epistemology’, which has been commodified as ‘discovery’ in contemporary ‘apps’ that assist users access various kinds of cultural texts (music, written texts, phatic/social media texts, etc). The media event of True Detective (as compared to the televisual text) is interesting as it dramatises the ‘detective work’ of this liminal epistemology itself. From the introduction of my True Detective essay:
If nothing else, True Detective clearly triggers meta-detective work by the audience. The show, its inter-textual references, and non-diegetic exegetical explanations of these references produced new edges of surprise and a new sense of expectation. For example, there is a folding of the crime fiction genre into existentialist horror and a topological transformation wrought upon both. Both genres frame a passage of discovery by the characters and audience. “Discovery” has become a buzzword in user-centred design to describe the design of platforms that assist users discover appropriate content, and this refers to the way users willingly embrace the delegated agency of “smart” interfaces. The liminal epistemology of discovery in meta-stable media assemblages pose answers to questions that haven’t yet been asked. The question isn’t simply asked of the characters of the show, but of the entire event itself as it repeated different elements of genres in different ways; in effect, the audience carries out meta-detective work.
The reason why I am excited about Groys’ work is that he has already isolated a similar problematic with regards to the revaluation of values. His focus so far is not animated by the same concerns as I am, but there is a similar problematic. I make it very clear that what I found the most interesting about the True Detective media event is that it is part of a broader constellation of cultural texts that are all, in different ways, working through this revaluation of values. From the introduction of my essay:
In the final section I develop meta in terms of what Sianne Ngai (2012) calls a minor aesthetic category, and in this case what characterises meta as a minor aesthetic category is the way any text, object or event that dramatises the suspension of cultural values. In Simondon’s terms, meta is an aesthetic category that refers to works that in some way repotentialise values that serve as the “preindividual norms” of value in a state of meta-stability ready to be potentialised in a multiplicity of ways (Combes 2013: 64). As I shall explore in detail, True Detective dramatises a conflict between systems of belief and cultural value through the figures of the two main characters, Rust and Marty. In this way, “meta” signals a threshold of value (or what Nietzsche (1968) calls “transvaluation”) more often associated with nihilism.
Engineers at Facebook have worked to continually refine the ‘Edgerank‘ algorithm over the last five or six years or so. They are addressing the problem of how to manage the 1500+ pieces of content available at any moment from “friends, people they follow and Pages” into a more manageable 300 or so pieces of content. Questions have been asked about how Edgerank functions from two related groups. Marketers and the like are concerned about ‘reach’ and ‘engagement’ of their content. Political communication researchers have been concerned about how this selection of content (1500>300) relies on certain algorithmic signals that potentially reduces the diversity of sources. These signals are social and practice-based (or what positivists would call ‘behavioral’). Whenever Facebook makes a change to its algorithm it measures its success in the increase in ‘engagement’ (I’ve not seen a reported ‘failure’ of a change to the algorithm), which means interactions by users with content, including ‘clickthrough rate’. Facebook is working to turn your attention into an economic resource by manipulating the value of your attention through your News Feed and then selling access to your News Feed to advertisers.
Exposure to ideologically diverse news and opinion on Facebook
Recently published research by three Facebook researchers was designed to ascertain the significance of the overall selection of content by the Edgerank algorithm. They compared two large datasets. The first dataset was of pieces of content shared on Facebook and specifically ‘hard’ news content. Through various techniques of text-based machine analysis they distributed these pieces of content along a single political spectrum of ‘liberal’ and ‘conservative’. This dataset was selected from “7 million distinct Web links (URLs) shared by U.S. users over a 6-month period between July 7, 2014 and January 7, 2015”. The second dataset was of 10.1 million active ‘de-identified’ individuals who ‘identified’ as ‘conservative’ or ‘liberal’. Importantly, it is not clear if they only included ‘hard news’ articles shared by those in the second set. The data represented in the appended supplementary material suggests that this was not the case. There are therefore two ways the total aggregate Facebook activity and user base was ‘sampled’ in the research. The researchers combined these two datasets to get a third dataset of event-based activity:
This dataset included approximately 3.8 billion unique potential exposures (i.e., cases in which an individual’s friend shared hard content, regardless of whether it appeared in her News Feed), 903 million unique exposures (i.e., cases in which a link to the content appears on screen in an individual’s News Feed), and 59 million unique clicks, among users in our study.
These events — potential exposures, unique exposures and unique clicks — are what the researchers are seeking to understand in terms of the frequency of appearance and then engagement by certain users with ‘cross-cutting’ content, i.e. content that cuts across ideological lines.
The first round of critiques of this research (here, here, here and here) focuses on various aspects of the study, but all resonate with a key critical point (as compared to a critique of the study itself) that the research is industry-backed and therefore suspect. I have issues with the study and I address these below, but they are not based on it being an industry study. Is our first response to find any possible reason for being critical of Facebook’s own research simply because it is ‘Facebook’?
Is the study scientifically valid?
The four critiques that I have linked to make critical remarks about the sampling method and specifically how the dataset of de-identified politically-identifying Facebook users was selected. The main article is confusing and it is only marginally clearer in the appendix but it appears that both samples were validated against the broader US-based Facebook user population and total set of news article URLs shared, respectively. This seems clear to me, and I am disconcerted that it is not clear to those others that have read and critiqued the study. The authors discuss validation, specifically point 1.2 for the user population sample and 1.4.3 for the validation of the ‘hard news’ article sample. I have my own issues with the (ridiculously) normative approach used here (the multiplicity of actual existing entries for political orientation are reduced to a single five point continuum of liberal and conservative, just… what?), but that is not the basis of the existing critiques of the study.
Eszter Hargittai’s post at Crooked Timber is a good example. Let me reiterate that if I am wrong with how I am interpreting these critiques and the study, then I am happy to be corrected. Hargittai writes:
The second paragraph above continues with a further sentence that suggestions that the sample was indeed validated against a sample of 79 thousand other FB US users. Again, I am happy to be corrected here, but this at least indicate that the study authors have attempted to do precisely what Hargittai and the other critiques are suggesting that they have not done. From the appendix of the study:
I am troubled that other scholars are so quick to condemn a study for not being valid when it does not appear as if any of the critiques (at the time of writing) attempt to engage with the methods but which the study authors tested validity. Tell me it is not valid by addressing the ways the authors attempted to demonstrate validity, don’t just ignore it.
What does the algorithm do?
A more sophisticated “It’s Not Our Fault…” critique is presented by Christian Sandvig. He notes that the study does not take into account how the presentation of News Feed posts and then ‘engagement’ with this content is a process where the work of the Edgerank algorithms and the work of users can not be easily separated (orig. emphasis):
What I mean to say is that there is no scenario in which “user choices” vs. “the algorithm” can be traded off, because they happen together (Fig. 3 [top]). Users select from what the algorithm already filtered for them. It is a sequence.**** I think the proper statement about these two things is that they’re both bad — they both increase polarization and selectivity. As I said above, the algorithm appears to modestly increase the selectivity of users.
And the footnote:
**** In fact, algorithm and user form a coupled system of at least two feedback loops. But that’s not helpful to measure “amount” in the way the study wants to, so I’ll just tuck it away down here.
A “coupled system of at least two feedback loops”, indeed. At least one of those feedback loops ‘begins’ with the way that users form social networks — that is to say, ‘friend’ other users. Why is this important? Our Facebook ‘friends’ (and pages and advertisements, etc.) serve as the source of the content we are exposed to. Users choose to friend other users (or Pages, Groups, etc.) and then select from the pieces of content these other users (and Pages, advertisements, etc.) share to their networks. That is why I began this post with a brief explanation of the way the Edgerank algorithm works. It filters an average of 1500 possible posts down to an average of 300. Scandvig’s assertion that “[u]sers select from what the algorithm already filtered for them” is therefore only partially true. The Facebook researchers assume that Facebook users have chosen the sources of news-based content that can contribute to their feed. This is a complex set of negotiations around who or what has the ability and then the likelihood of appearing in one’s feed (or what could be described as all the options for organising the conditions of possibility for how content appears in one’s News Feed).
The study is testing the work of the algorithm by comparing the ideological consistency of one’s social networks with the ideological orientation of the stories presented and of the news stories’ respective news-based media enterprises. The study tests the hypothesis that your ideologically-oriented ‘friends’ will share ideological-aligned content. Is the number of stories from across the ideological range — liberal to conservative — presented (based on an analysis of ideological orientation of each news-based media enterprise’s URL) different to the apparent ideological homophily of your social network? If so, then this is the work of the algorithm. The study finds that the algorithm works differently for liberal and conservative oriented users.
For example, that the newsfeed algorithm suppresses ideologically cross cutting news to a non-trivial degree teaches individuals to not share as much cross cutting news. By making the newsfeed an algorithm, Facebook enters users into a competition to be seen. If you don’t get “likes” and attention with what you share, your content will subsequently be seen even less, and thus you and your voice and presence is lessened. To post without likes means few are seeing your post, so there is little point in posting. We want likes because we want to be seen.
‘Likes’ are only signal we have that helps shape our online behaviour? No. Offline feedback is an obvious one. What about the cross-platform feedback loops? Most of what I talk about on Facebook nowadays consists of content posted by others on other social media networks. We have multiple ‘thermostats’ for aligning the appropriate and inappropriateness of posts in terms of attention, morality, sociality, cultural value, etc. I agree with Jurgenson, when he suggests that Jay Rosen’s observation that “It simply isn’t true that an algorithmic filter can be designed to remove the designers from the equation.” A valid way of testing this has not been developed yet.
The weird thing about this study is that from a commercial point of view Facebook should want to increase the efficacy of the Edgerank algorithms as much as possible, because it is the principle method for manipulating the value of ‘visibility’ of each user’s News Feed (through frequency/competition and position). Previous research by Facebook has sought to explore the relative value of social networks as compared to the diversity of content, this included a project that investigated the network value of weak tie social relationships.
Effect of Hard and Soft News vs the Work of Publics
What is my critique? All of the critiques mention that the Facebook research, from a certain perspective, has produced findings that are not really that surprising because they largely confirmed how we already understand how people choose ideological content. A bigger problem for me is the hyper-normative classification of ‘hard’ and ‘soft’ news as it obscures part of what makes this kind of research actually very interesting. For example, from the list of 20 stories provided as an example of hard and soft news, at least two of the ‘soft’ news stories are not ‘soft’ news stories by anyone’s definition. From the appendix (page 15):
Protesters are expected to gather in downtown Greenville Sunday afternoon to stage a Die In along Main Street …
Help us reach 1,000,000 signatures today, telling LEGO to ditch Shell and their dirty Arctic oil!
There are at least two problems for any study that seeks to classify news-based media content according to normative hard and soft news distributions when working to isolate the how contemporary social media platforms have affected democracy:
1. The work of ‘politics’ (or ‘democracy’) does not only happen because of ‘hard news’. This is an old critique, but one that has been granted new life in studies of online publics. The ‘Die-In’ example is particularly important in this context. It is a story on a Fox News affiliate, and I have only been able to find the exact words provided in the appendix by the study authors to refer to this article on Fox News-based sites. Fox News is understood to be ‘conservative’ in the study (table S3 of appendix), and yet the piece on the ‘Die-In’ protest does not contain any specific examples of conservative framing. It is in fact a straightforward ‘hard news’ piece on the protest that I would actually interpret as journalistically sympathetic towards the protests. How many stories classified as ‘conservative’ because they appear on a Fox News-based URL? How many other allegedly ‘soft news’ stories were not actually soft news at all?
2. Why is ‘cross cutting’ framed only along ideological lines of content and users, when it is clear that allegedly ‘soft news’ outlets can cover ‘political topics’ and that more or less impact ‘democracy’? In the broadcast and print-era of political communication, end users had far less participatory control over the reproduction of issue-based publics. They used ‘news’ as a social resource to isolate differences with others, to argue, to understand their relative place in the world, etc. Of profound importance in the formation of online publics is the way that this work (call it ‘politics’ or not) takes over the front stage in what have been normatively understood as non-political domains. How many times have you had ‘political’ discussions in non-political forums? Or more important for the current study, how many ‘Gamergate’ articles were dismissed from the sample because the machine-based methods of sampling could not discern that they were about more than video games? The study does not address how ‘non-political’ news-based media outlets become vectors of political engagement when they are used as a resource by users to rearticulate political positions within issue-based publics.
Nearly every single student in my big Introduction to Journalism lecture knew what I was talking about when I mentioned #thedress. I used it as a simple example to illustrate some core concepts for operating in a multi-platform or convergent news-based media environment.
Multi-Platform Media Event
Journalists used to be trained to develop professional expertise in one platform. Until very recently this included radio, television or print and there was a period from the early to mid-2000s when ‘online’ existed as a fourth category. Now ‘digital’-modes of communication are shaping almost all others. We’ve moved from a ‘platform only’ approach to a ‘platform first’ approach — so that TV journalists also produces text or audio, writers produce visuals, an so on — and what is called a ‘multi-platform’ (or ‘digital first’, ‘convergent’ or ‘platform free’) approach.
When with think ‘multi-platform’, we think about how the elements of a story will be delivered across media channels or platforms:
Live – presentations
Social – Facebook, Twitter, Youtube, etc.
Web – own publishing platform, podcast, video, etc.
Mobile – specific app or a mobile-optimised website
Television – broadcast, narrowcast stream, etc.
Radio – broadcast, digital, etc.
Print – ‘publication’
‘Platform’ is the word we use to describe the social and technological relation between a producer and a consumer of a certain piece of media content in the act of transmission or access. In a pre-digital world, transmission or delivery were distinct from what was transmitted.
Thinking in terms of platforms also incorporates how we ‘operate’ or ‘engage’ with content via an ‘interface’ and so on. Most Australians get their daily news from the evening broadcast television news bulletin. Recent figures indicate that most people aged 18-24 actually get their news about politics and elections from online and SNS sources, compared to broadcast TV.
#thedress is a multi-platform media event. It began on Tumblr and then quickly spread via the Buzzfeed post to Twitter and across various websites belonging to news-based media enterprises. It only makes sense if the viral, mediated character of the event is taken into account. #thedress media event did not simply propagate, it spread at different rates and at different ways. The amplification effect of celebrities meant #thedress propagated across networks that are different orders of magnitude in scale. Viral is a mode of distribution, but it also produces relations of visibility/exposure.
New News and Old News Conventions
Consumers of news on any platform expect the conventions of established news journalism. What are the conventions of established news journalism?
The inverted pyramid
Grammar: Active Voice, Tense
When we look at #thedress multi-platform media event we see different media outlets covered the story in different ways. Time magazine wrote the most conventional lead out of any that I have seen; the media event is the story:
I’ve only include the head, intro and first par for Time and Cosmo and you can see already they are far more verbose compared to Buzzfeed’s original post. The original Buzzfeed post rearticulated a Tumblr post, but with one important variation:
What Colors Are This Dress?
There’s a lot of debate on Tumblr about this right now, and we need to settle it.
This is important because I think I’m going insane.
Tumblr user swiked uploaded this image.
There’s a lot of debate about the color of the dress.
So let’s settle this: what colors are this dress?
68% White and Gold
32% Blue and Black
The Buzzfeed post added an ‘action’: the poll at the bottom of the post. Why is this important?
Buzzfeed, Tumblr and the Relative Value of a Page View
Some of its sponsored “story unit” ad units have clickthrough rates as high as 4% to 5%, with an average around 1.5% to 2%, BuzzFeed President Jon Steinberg says. (That’s better than the roughly 1% clickthrough rate Steinberg says he thought was good for search ads when he worked at Google.) BuzzFeed’s smaller, thumbnail ad units have clickthrough rates around 0.25%.
At BuzzFeed our mobile traffic has grown from 20% of monthly unique visitors to 40% in under a year. I see no reason why this won’t go to 70% or even 80% in couple years.
Importantly, Buzzfeed’s business model is still organised around displaying what used to be called ‘custom content’ and what is now commonly referred to as ‘native advertising’ or even ‘content marketing’ when it is a longer piece (like these Westpac sponsored posts at Junkee).
On the other hand, Tumblr is a visual platform; users are encouraged to post, favourite and reblog all kinds of content, but mostly images. For example, .gif-based pop-culture subcultures thrive on tumblr and tumblr icons are those that perform gestures that are easily turned into gifs (Taylor Swift) or static images (#thedress).The new owners of Tumblr, Yahoo, are struggling to commercialise Tumblr’s booming popularity.
I had a discussion with the Matt Liddy and Rosanna Ryan on Twitter this morning about the relative value of the 73 million views of the original Tumblr post versus the value of the 38 million views of the Buzzfeed post. Trying to make sense of what is of value in all this is tricky. At first glance the 73 million views of the original Tumblr post trumps the almost 38 million views of the Buzzfeed post, but how has Tumblr commercialised the relationship between users of the site and content? There is no clear commercialised relationship.
Buzzfeed’s business model is premised on a high click-through rate for their ‘native advertising’. Of key importance in all this is the often overlooked poll at the bottom of the Buzzfeed post. Almost 38 million or even 73 million views pales in comparison to the 3.4 million votes in the poll. Around 8.6% of the millions of people who visited the Buzzfeed article performed an action when they got there. This may not seem as impressive an action as those 483.2 thousand Tumblr uses that reblogged #thedress post, but the difference is that Buzzfeed has a business model that has commercialised performing an action (click-through), while Tumblr has not.
Last week I delivered the first lecture in our Introduction to Journalism unit. I am building on the material that my colleague, Caroline Fisher, developed in 2014. One of the things about teaching journalism is that every example has to be ‘up to date’. One of the things that Caroline discussed in the 2014 lecture were the predictions for 2014 as presented by the Nieman Lab.
Incorporating these predictions into a lecture is a good way to indicate to students what some professionals and experts think are going to be the big trends, changes and events in journalism for that year. (The anticipatory logic of predictions about near-future events has become a genre of journalism/media content that I briefly discuss in a forthcoming journal article. See what I did there.)
To analyse the the 65 predictions for 2015 in a lecture that only goes for an hour would be almost impossible. What I did instead was to carry out a little exercise in data journalism to introduce students to the practical concepts of ‘analytics’, ‘website scraping’, and the capacity to ‘tell a story through data’.
I created a spreadsheet using Outwit Hub Pro that scraped the author’s name, the title of the piece, the brief one or two line intro and the number of Twitter and Facebook shares. I wanted to know how many times each prediction had been shared on social media. This could then serve as a possible indicator of whether readers though the prediction was worth sharing through at least one or two of their social media networks. By combining the number of shares I could then have a very approximate way to measure which predictions readers of the site had the most value.
I have uploaded the table of the Nieman Lab Journalism Predictions 2015 to Google Drive. The table has some very quick and simple coding of each of the predictions so as to capture some sense of what area of journalism the prediction is discussing.
The graph resulting from this table indicates that there were four predictions that were shared more than twice the number of times compared to the other 61 predictions. The top three stories had almost three times the number of shares.
Here are the four stories with the total number of combined shares:
I guess I could pivot here to talk about the future of news in 2015 being about mobile and personalization. (I would geek out about both immensely.) I suppose I could opine on how the reinvention of the article structure to better accommodate complex stories like Ferguson will be on every smart media manager’s mind, just as it should have been in 2014, 2013, and 2003.
But let’s have a different kind of real talk, shall we?
My prediction for the future of news in 2015 is less of a prediction and more of a call of necessity. Next year, if organizations don’t start taking diversity of race, gender, background, and thought in newsrooms seriously, our industry once again will further alienate entire populations of people that aren’t white. And this time, the damage will be worse than ever.
It was a different kind of prediction compared to the others on offer. Most people who work in the news-based media industry have been tasked with demonstrating a permanent process of professional innovation. Edwards piece strips back the tech-based rhetoric and gets at the heart of what media organizations need to be doing so as to properly address all audiences. “The excuse that it’s ‘too hard’ to find good journalists of diverse backgrounds is complete crap.”
The second most shared piece, on the limitations of over-relying on Facebook as a driver of traffic, fits perfectly with the kind of near-future prediction that we have come to expect. Gnomic industry forecasting flips the causal model with which we are familiar — we are driven by ‘history’ and it is the ‘past’ (past traumas, past successes, etc) that define our current character — so that it draws on the future as a kind of tech-mediated collective subconscious. Rather than being haunted by the past, we are haunted by possible futures of technological and organisational change.
Algorithms are increasingly being deployed to make decisions where there is no right answer, only a judgment call. Google says it’s showing us the most relevant results, and Facebook aims to show us what’s most important. But what’s relevant? What’s important? Unlike other forms of automation or algorithms where there’s a definable right answer, we’re seeing the birth of a new era, the era of judging machines: machines that calculate not just how to quickly sort a database, or perform a mathematical calculation, but to decide what is “best,” “relevant,” “appropriate,” or “harmful.”
Media editor of The Australian, Sharri Markson, has produced an article titled ‘Activism a threat to journalism‘. In it she draws on sources to argue that ‘activist journalism academics’ on ‘social media’ are a threat to journalism. She paraphrases her boss and Australian newspaper editor, Chris Mitchell:
Editor-in-chief of The Australian, Chris Mitchell, said the greatest threat to journalism was not the internet or governments and press councils trying to limit free speech, but the rise of the activist journalist over the past 25 years and the privileging of the views of activist groups over the views of the wider community.
Worse than the figure of the ‘activist journalist’ is the ‘modern journalism academic’. Here Markson introduces a Mitchell quote so as describe the ‘modern journalism academic’ as someone with opinions on political issues:
Mr Mitchell, who has edited newspapers for more than 20 years, said media academics who were vocal about ideological issues on social media were part of the problem.
“This is at the heart of my disdain for modern journalism academics. And anyone who watches their Twitter feeds as I do will know I am correct,’’ he said.
Tens of thousands of people, including journalism students and those starting their career in the industry, follow media academics Jenna Price, Wendy Bacon and journalist Margo Kingston on Twitter. All are opinionated on political issues.
Through its Media section the Australian newspaper is running a small-scale ‘moral panic’ about the loss of efficacy of legacy media outlets, like the print-based Australian newspaper. Most of the people who work at the Australian newspaper have been to university and would’ve more than likely come across the concept of a moral panic. Even if they haven’t, as savvy media operators that should be familiar with the concept.
The concept of the ‘moral panic’ once belonged to the academic discipline of sociology, but has now largely leaked into everyday language. A moral panic is a diagnostic tool used to understand how fears and anxieties experienced by social group often about social change is projected onto and becomes fixated around what is called a ‘folk devil’.
A ‘folk devil’ is a social figure who may be represented by actual people, but functions to gather fear and anxiety. I have a book chapter on the folk devil figure of the ‘hoon’. There are actual ‘hoons’ who are a road safety issue, but the hoon moral panics that swept across Australia 10 years ago were completely out of proportion to the actual risk presented by hoons. The figure of the hoon represented fears and anxieties about how young people use public space particularly in areas with high retiree and tourist populations.
Clearly, the ‘activist journalist’ and ‘modern journalism academic’ are the folk devil figures. What fears and anxieties do ‘activist journalists’ and ‘modern journalism academics’ represent? ‘Social media’ is used as a collective term in Markson’s piece to describe technologies and social practices that threaten not only the commercial existence of the Australian newspaper, but also its existential purpose. As Crikey reported last week, the Australian newspaper is losing money hand over fist, but I think this ongoing effort to attack ‘activist journalists’ and ‘modern journalism academics’ indicates that the anxiety has a greater purchase than mere commercial imperatives in the Australian newspaper workplace.
Markson has been a vocal activist for print-based publication and it is clear from her advocacy workon social media that she is a ‘print media’ enthusiast. Indeed, Markson and Mitchell could be described as what are the ‘moral entrepreneurs‘ of the ‘moral panic’ in this particular example. A ‘moral entrepreneur’ is a person or group of people who advocate and bring attention to a particular issue for the purposes of trying to effect change. In traditional moral panic theory this is largely local politicians who try to effect legislative change to compensate for the social changes that triggered the moral panic in the first place.
The Australian newspaper’s ongoing response to the perceived existential threat of ‘social media’ (as an inaccurate collective term to describe far more complex and longer term shifts in the media industry) is a useful example for thinking about the cyclical character of these outbursts. They are small-scale moral panics because they never really spread beyond a limited number of moral entrepreneurs. The latest round is merely another example of the media-based culture wars that began with the so-called ‘media wars‘ in the late 1990s. Again, journalism academics were central in the conflict over what counted as ‘journalism’ and/or ‘news’. More recently, the Australian newspaper attacked journalism programs and their graduates.
The ‘Outrage Cycle’
The concept of a ‘moral panic’ is a bit clunky and doesn’t really capture the cyclical character of these ideological battles over perceived existential threats. Creator of the ‘moral panic’ concept, Stanley Cohen, included some critical comments about the concept as a revised introduction to the 2002 third edition of his iconic Folk Devils and Moral Panics book. About the possibility of a “permanent moral panic” Cohen writes:
A panic, be defintion, is self-limiting, temporary and spasmodic, a splutter of rage which burns itself out. Every now and then speeches, TV documentaries, trials, parliamentary debates, headlines and editorials cluster into the peculiar mode of managing information and expressing indignation that we call a moral panic. Each one may draw on the same stratum of political morality and cultural unease and — much like Foucault’s micro-systems of power — have a similar logic and internal rhythm. Successful moral panics owe their appeal to their ability to find points of resonance with wider anxieties. But each appeal is a sleight of hand, magic without a magician. (xxx)
A useful model for understanding the cyclical character of the relation between anxiety (or what we call ‘affect’), greater media attention (or what we call, after Foucault, ‘visibility’) and an exaggerated sense of social norms and expectations is Gartner’s ‘Hype Cycle’ model.
It is not a ‘theoretical’ or even a ‘scientific’ tool; rather, it serves as a kind of rule of thumb about the reception of technological change for the purposes of creating business intelligence. New technologies tend to be hyped so take this into account when making business decisions about risks of investment. (Each year I use the ‘Hype Cycle’ to introduce my third year unit on technological change ; the way it represents technology is useful for understanding social relations and technology beyond technology being an ‘object’.) There is something similar going on with the Australian newspaper’s constant preoccupation with other journalists and in particular the role of journalism academics in society. Rather than the giddy ‘hype’ of the tech press and enthusiasts about technological change, the Australian newspaper’s cycle is organised around ‘outrage’. The Australian newspaper’s ‘Outrage Cycle’ is a useful way to frame how Western societies constantly mobilise to engage with perceived existential threats. The actual curve of the ‘Hype CYcle’ itself is less important than the cyclical character of trigger and response, which is also apparent in ‘moral panic’ theory:
I’ve changed the ‘zones’ of the Hype Cycle. ‘Maturity’ did not seem like the most appropriate measure of the X-axis, so I changed it to ‘time’ which Gartner also sometimes uses. I’ve made a table for ease of reference:
Peak of Inflated Expectations
Peak of Confected Outrage
Trough of Disillusionment
Trough of Realism
Slope of Enlightenment
Slope of Conservatism
Plateau of Productivity
Plateau of Social Norms
Existential threat: In the case of the Australian newspaper, the existential threat is not so much activist journalists and modern journalism academics, but the apparent dire commercial position of the newspaper and the accelerated decline in social importance of a national newspaper. The world is changing around the newspaper and it currently survives because of cross-funding arrangements from other sections of News Corp. The moral entrepreneurs in this case are fighting for the very existence of ‘print’ and the institutional social relations that ‘print’ once enjoyed. A second example of this involves ‘online piracy’, which serves as a perceived existential threat to the current composition of media distribution companies.
Peak of Confected Outrage: It is unclear who is actually outraged besides employees of News Corp about so-called ‘activist journalists’ and ‘modern journalism academics’ in general. There are specific cases, just like with ‘moral panics’, where specific people have triggered the ire of some social groups. They serve as representative ‘folk devils’ for an entire social identity. Similarly, ‘pirates’ serve as an example of ‘bad internet users’ who are part of the disruptions of the legacy media industry. There is a more sophisticated point to be made about reporting on ‘outrage’ and other affective states like ‘fear’ and ‘anxiety’. They become their own sources of newsworthiness.
Trough of Realism: In the case of the Australian newspaper, this is where legacy media advocates face up to the unfortunate reality of the shifting media industry. It is not clear to me, at least in this example, that this will actually happen. (Perhaps after the Australian newspaper folds?) In terms of ‘online piracy’ facing reality includes companies like Foxtel currently working to create online client versions of their pay TV business. It is basically at this point that proponents have to ‘face reality’.
Slope of Conservatism: In Gartner’s original version, technologies become adopted and companies learn how to use them appropriately. In the ‘Outrage Cycle’ the Slope of Conservatism is ironically named as it signals social change. In some ways, Markson’s advocacy of ‘print’ is a bad example of this. A better example is the way sports fans learn how to adapt to the commodification of broadcast sporting events.
Plateau of Social Norms: The constant change in social values and relations that have characterised Western societies for the last 300 years continues unabated, indicated by the increasing ‘liberalisation’ of normative social values, but societies often pass thresholds of organisational composition where certain norms are dominant. Heterosexual patriarchal social values and racist social values were normative up until the postwar period in Australia, then they began a very slow process of changing and we are still in the midst of these shifts. Most people who work in the media industry are learning to operate in the new norms that characterise contemporary expectations regarding the production, distribution/access and consumption of media and journalistic content. Recent examples of this include the popularity of the ‘home theatre’ as the most recent evolution of domestic cinema culture that become part of mass popular cultures with the VCR.
Major media corporations and tech giants have become bogged down in nymwars, post-hoc jerry-rigging and outright comment bans as they attempt to erase conflict around perenially divisive topics. All the while, as media companies are all too happy to trade on clickbait and outrage, there’s a suspicion that they have appropriated and mobilised the figure of the troll in order to constrain a new outpouring of political speech. Trolling has perhaps displaced pornography as the obscenity which underwrites the demand that the Internet be brought under control.
In the midst of social media’s perpetual flurries of outrage, we teach one another that the range of acceptable opinion is small, that we are individually responsible for comporting ourselves within these limits, and that the negative consequences are unpredictable, and potentially catastrophic. Accepting cues – from media, government and other authorities – about the dangers of incivility and extremism, we monitor each other’s conduct, ensuring that it doesn’t cross any arbitrary lines.
We can read the perpetual Outrage Cycle of the Australian newspaper as a machine for the production of new normative social values. Without being subsidised by other business areas of the News Corp enterprise, the Australian newspaper would be out of business, so to say that the Australian will inevitably fail is to miss the point that it is already in a state of constant ‘fail’. Unless someone thinks that the Australian newspaper will actually become profitable again (and will do so while its editor-in-chief and media editor are advocating for ‘print’), the social function of the Australian newspaper is not to make money as a commercial journalistic enterprise but to serve a social role that reinforce what its employees perceive to be normative social values.
The Australian newspaper and other News Corp print-based products seemed to be currently organised around using this ‘Outrage Cycle’ as a business model. Isolate a perceived existential threat (religion, class difference, education, etc.) and then represent this on the front page of newspapers in such a way as to create feelings of fear, anxiety and outrage in the community. We know that they do not aim to represent and report on this fear, anxiety and outrage, because otherwise their front pages would be full of articles about readers of their own newspapers.