A couple days ago I wrote up my description of the Information Intervention Chain. One of the points there was that work on each layer decreases the load on the layers below, and helps cover some of the errors not caught in the layers above.
Here’s a simple example, where a user has has responded to someone talking about ivermectin. Their impression — if we take this user at their word, and in this case I do — is that the NIH has started recommending ivermectin.
Now this is false, and I suppose some might say to just ban such things altogether. The NIH is not recommending the use of ivermectin for COVID-19. This is a fact. But I doubt we want to be in the business of policing every small, non-viral, good faith but confused reply people make on social media. Moderation is important, but it needs to be well targeted.
So next we get to the layer of interface. And here we find something pretty interesting. The user believes at least two wrong things:
That this is a recent (late summer/fall) article on the use of ivermectin which negates previous guidance
That this article represents a statement by the NIH
Take a moment to look at the post. Where would they get such ideas?
The fact is that their assumptions are quite reasonable given the failures of the interface to provide context. The article linked here is not from the NIH but rather from the American Journal of Therapeutics. It looks like it comes from the NIH, and that’s largely because the Twitter card (as well as the Facebook card, etc) highlights the NIH.gov address as the source, a side effect of the article being available through a database that is run through the NIH. The card, in this case, actively creates the wrong impression.
The second point — is it new? Note that when the link is shared there is no indication of the publication date of the article. So this article was actually published in the spring, and is, at best, out of date at this point. But Twitter chooses to not make the date of the article visible in the shared card. And that’s not a dig on just Twitter here — at least as far as I can tell, the PubMed page doesn’t expose the publication date or the journal name at the meta level. Somewhat shockingly there seems to be no Facebook or Twitter-specific meta info at all. Even if Twitter wanted to make publication and publication date more visible, it’s not clear the site gives them the information they would need to do it.
Now once you click through, you should be good. Should be good, but I’ll get to that in a moment.
Here’s the good news, if you click the link to the page, you see some of the information of which this person was unaware: the journal name, the fact that it’s on PubMed, the date at the top. But even here we are undone by confusing interface choices.
That banner at the top? From the NIH, supposedly? What does it say?
It says that this is the Library of Medicine by the National Institutes of Health, and you’re in luck, because there’s some important COVID-19 guidance below!
Wait, that’s not what a big banner with an exclamation point saying “COVID-19 Information” means? So tell me what an average person is supposed to think an exclamation-marked heading on an NIH site saying “COVID-19 Information” indicates?
It’s supposed to mean that what is below it is not official?
Well, good luck with that.
People keep wanting to talk about how people are hopelessly biased, or cynical, or post-truth, or whatever. And sure, maybe. But how would we know? How would we possibly know when someone engaging in a plain text reading of both what Twitter and the NIH is providing them here would come to this exact conclusion, that the NIH is now recommending they take ivermectin?
Now, can the layer below the interface intervention — in this case, the individual layer of educational interventions — clean this up? Well, educators have been trying to. Understanding things like the difference between an aggregation site like PubMed and a publisher like the American Journal of Therapeutics are things we teach students. But coming back to the “load” metaphor, it would make a lot more sense to clean this mess up at the interface layer, at least for a major site like PubMed. I mean, I can try to teach several billion people what PubMed is, or, alternatively, Twitter, Facebook, and PubMed itself could choose to make it clear what PubMed is at the interface layer, which would allow education to focus limited time on more difficult problems.
Nothing — not in any of the layers — is determinative in itself. But improving the information environment means chipping away at the things that can be done, in each of the layers, until the problems left are truly only the hard ones. We still aren’t anywhere near to that point.
Some notes I just wanted to get down. There are four places where information interventions can be applied.
Moderation/Promotion. A platform always makes decisions on what to put in front of a user. It can decide to privilege information that is more reliable on one or another dimension, or to reduce the dissemination of unreliable or harmful information, either through putting limits on its virality or findability, or through removal. There are clearly things which need to be dealt with at this level, though it is notable that most arguments happen here.
Interface. Once a platform decides to provide a user information, it can choose to supply additional context. This is a place where there has been a mixed bag of interventions. Labeling is an example of one that has often been used in relatively ineffective ways. Other more specific interventions have better effects — for example, letting people know a story deceptively presented new is actually old.
Individual. This is (usually) the realm of educational interventions. We can choose to build in the user capabilities to better assess information they are provided. This might be specific understandings about information-seeking behavior, or more general understandings about subjects in question or the social environment in which they are making judgments (including examining biases they may hold).
Social. Consuming information via social software is not an individual endeavor, but a process of community sense-making. Social interventions seek to empower communities of users to get better at collective sense-making and promotion of helpful information. Some of these interventions may involve platform actions — whatever one thinks of a recent Facebook proposal to identify knowledgeable members in Facebook groups, it is clearly a social intervention meant to aid in collective sense-making. Other interventions may not involve platforms at all — teaching members of communities to correct error effectively, for example, does not require any additional platform tools, but may have substantial impact. Teaching experts to communicate more effectively on social media may bring specific expertise in to communities which desire it, and teaching community leaders the basics of a given subject can provide expertise to those with influence.
The Intervention Chain
People sometimes argue where interventions should be applied. For instance, there is a valid argument that deplatforming figures that are repeatedly deceptive may do more net good than interface interventions or media literacy. Likewise, many scholars point out without strengthening impacted communities or addressing underlying social drivers of bad information little progress can be made.
I think it’s more helpful to see the various layers as a chain. Ultimately, the final level is always social — that’s where messages get turned (or not turned) into meaning and action. And it’s still a place where interventions are relatively unexplored.
But that doesn’t diminish the value of the other layers. Because each layer involves intensive and sometimes contentious work, it relies on the layers of intervention above to reduce the “load” it has to deal with. For instance, the choice between media literacy and moderation is a false choice. Media literacy can be made less cognitively costly for individuals to apply, but there still is a cost. If obvious bullshit is allowed to flow through the system unchecked — if, say, every third post is absolute fantasy — media literacy doesn’t stand a chance.
Likewise, proponents of social interventions often point out the flaws of the individual layer — people are social animals of course, and a technocratic “check before you share” doesn’t reckon with the immense influence of social determinants on sharing and belief. And it’s true that solutions at the individual layer are a bit of a sieve, just as are solutions in the layers above. But we need to stop seeing that as a weakness. Yes, taken individually, interventions at each layer are leaky. But by filtering out the most egregious stuff they make the layers below viable. By the time we hit social interventions, for example, we are are hopefully dealing with a smaller class of problems unsolvable by the other layers. Likewise, moderation interventions can afford to be a bit leaky (as they have to be to preserve certain social values around expression) if subsequent layers are healthy and well-resourced.
Anyway, this is my attempted contribution to get us past the endless cycle where people involved with theorizing one level explain to people theorizing the other levels why their work is not the Real Work (TM). In reality, no link in the intervention chain can function meaningfully without the others. (And yes, I am mixing a “chain” metaphor with a “layers” metaphor, but it’s a first go here.)
In a future post I hope to talk about promising interventions at each level here.
People have a lot of stuff they can share or attend to online.
In order to efficiently create and process content we look at things like “evidence” through tropes
Tropes, not narratives or individual claims, are the lynchpin of activism and propaganda, whether true or false, participatory or not. They are more persistent than claims, more compelling than narrative.
The success of a given trope is often based on its “fit” with the media, events, and data around the event (the “field”). A trope must be compelling but also fit the media available to creators. In participatory propaganda (see Wanless and Berk) tropes must be productive.
In participatory work, productive tropes are often adopted based on their productivity, and then retconned to a narrative. Narrative-claim fit is far less important than trope-field fit.
A key indication something is a trope is it can be used across multiple domains — that is they can be used to advance a variety of different claims.
Today I’m going to talk about how effective fact-checkers of misinformation also think in tropes in order to debunk nonsense, even if they don’t use that language to describe what they do. I’ll also suggest that making that way of thinking more explicit to readers might make readers more equipped to handle novel misinformation.
But first I wanted to talk about what happens now in terms of platform interventions and end-user interpretation. During the 2020 election, while working a rapid response effort, this tweet came across my radar. It was pulled up as part of an automated Twitter search I had set up for “throwing” + “ballots”.
I came across this about ten minutes after it was posted, and had a ticket in on it about 5 minutes after that. It was an amazing stroke of luck, really, to come upon it that early. I knew it was going to rack up real numbers, and over the next 45 minutes it did, until it was confirmed with the folks in Erie that this person did not, in fact, work in Erie. They couldn’t be a poll worker because they were not even a registered voter.
During that the period in between discovery and debunking, in the absence of official (dis)confirmation, people tried other things. They looked at the Instagram feed, trying to determine the high school or college the poster came from. Looked for other satirical posts. Tried to message the poster. And so on. This is the process of fact-checkers, and they are good at what they do. At the same time, there was something very strange about it, watching the reshares of the post tick up at astonishing rates while evidence was compiled. Because if you had offered any fact-checker 100 to 1 odds on whether this was fake, they would have taken them. It was obviously fake. Not just because it was unlikely that anyone would advertise a crime of this sort on Instagram. It was likely satire gone wrong because we had seen this happen exactly this way before.
It had happened in 2016, for example, which was why I had my scanner looking for this in the first place. Here it’s a satirical post about a postal worker, but same thing:
This post spiraled out of control, being promoted as an example of open fraud by Gateway Pundit and Rush Limbaugh. Here’s Limbaugh on his program back then:
So you’ve got a postal worker out there admitting he’s opening absentee ballots that have been mailed in and he’s just destroying the ones for Trump. What happens if he opens one up for Hillary, gotta reseal it? I guess they don’t care, what does it matter, as long as it says Hillary on it, what do the Democrats care where it came from? It could be postmarked Mars and they’ll take it.
This isn’t a case of a bit of misunderstanding blown out of proportion. It was a big misunderstanding in 2016. People really believed this, and generated so many outraged calls that the Post Office (I guess in some foreshadowing of what would happen in 2020) had to issue a statement:
Back to 2020 and the “poll worker throws away ballots”. A week after I found this, it would happen in a TikTok video, again — satire/trolling showing a “poll worker” throwing out ballots shared as fact (here reproduced on Instagram) and again, shared to hundreds of thousands of people (maybe millions?) as true.
As far as tropes, satire/trolling of this type is an interesting case (as is completely faked news) as it requires no “field” really, since it is completely fabricated. But it does require a knowledge of the existing tropes. As we mentioned in the first installment of this, the “public official discards ballots” trope is well established, especially in conservative circles, and when certain partisans see an embodiment of that trope via a tweet or a video they immediately comprehend it, share it, etc. The skids are greased and the trolling slides right through the system.
But my larger point is this — in many cases, even though fact-checkers go through the steps debunk something but they already have really solid plausibility judgments about whether it is likely to be fake. And it’s not necessarily because they are better critical thinkers, or have an encyclopedic knowledge of election oversight procedures. It’s because they have seen the same trope before, over and over, and know the ways in which it is likely to come up empty.
Let me give a somewhat ridiculous example. Perhaps you are a person who is blessed enough to not know the theory that Joe Biden has been replaced by a Body Double. (Yes, it’s a QAnon thing).
Here’s a picture that’s “evidence”. Joe Biden used to be left-handed, and now he’s right handed.
I’m sure it wouldn’t take you more than 20 seconds to figure out what’s going on here, but the average fact-checker has solved this before they’ve even finished reading the claim.
“Picture is reversed,” they say. “Check out how the handkerchief pocket’s on the wrong side.”
Are they Sherlock Holmes reborn, that they can literally process this in under a second?
No, of course not. They’ve just seen this trope before, and they know its specific bag of tricks. Here is the same “body double forgets what hand to use!” trope used against the President of Nigeria:
The result after checking? Flipped photograph. And we also saw this in 2016, where pictures of Clinton before and after her collapse at a 9/11 event showed “subtle differences in her hairstyle and face” indicating (supposedly) that it might really be a body double:
So, Body Double? Or…
Yes, it turns out that different sides of your face look different.
This is one — just one — of maybe about two dozen things you keep in mind when looking at instances of the Body Double conspiracy trope. Consider this random bag of big and small issues with comparing photographs, paired with a body double conspiracy where I’ve seen it exploited (not comprehensive by any means, just from memory)
Camera angle and lighting can make the same person look radically different (Derek Chauvin, too many others to count)
When a high resolution photo is compared to a low resolution one, a person looks different (Hillary Clinton)
Women in particular can appear to change height due to footwear (Melania Trump, Hillary Clinton, Avril Lavigne)
As we grow older our our eye sockets, nose and upper jaw continue to change, and ears lengthen at a rate of a millimeter every four or five years (Paul McCartney, Avril Lavigne, Joe Biden)
Face-lifts or other surgery can alter the appearance of the earlobe (Joe Biden, President Muhari)
Skin blemishes sometimes go away, are removed, or airbrushed out (Avril Lavigne)
Stills from video (especially when photographed on a TV) often create longer or rounder faces due to distortion (Derek Chauvin, Melania Trump, Paul McCartney)
Lefties often use their non-dominant hand for certain tasks (Paul McCartney)
An average person might be able to come to all these through a rational process, but for a fact-checker familiar with the trope and its more popular instantiations it’s likely far more automatic. In fact, you can see that the two sides of this essentially work the same list. The conspiracist goes down the mental list looking for signs of changed height, shifts in dominant hand, changes to the shape of the ears, photos where the face seems longer or shorter and sees if any of these differences can be found in the “field” of photos available. Those things are surfaced, wrapped in the trope, and disseminated. Then the fact-checker goes through the same mental list but from the other side of things: looking at the way the different types of “evidence” associated with this trope (earlobes, dominant hand, etc) tend to pan out. E.g. “Yeah, this is the old Paul McCartney’s ears are different thing — you can’t compare old and young photos for that.” They check everything of course, but they don’t start from scratch, they start from an understanding of the sorts of aspect of the field the trope tends to exploit. The creator uses their knowledge of the trope to construct, and the fact-checker uses their knowledge of the trope to deconstruct.
Plausibility judgments and discourse rules
A bit of a detour, but I promise it will make sense in a minute. As part of a larger argument in his recent book The Knowledge Machine, Michael Strevens points out a bit of a misconception about science. Or perhaps it’s a paradox?
Scientists must argue their ideas without any references to the ways in which those ideas are personally plausible to them, or reference to their opinions of the competence of person arguing against them. The rule is that the argument must be focused on the data, and it has to be that way for science to advance. This discourse norm is what allows science to progress. In order to make my case I have to produce evidence that you can then use to make yours.
The misconception though is this — because the norm does not allow the use of plausibility judgments (e.g. in the absence of evidence, do I think this is true or not?) it is often assumed that the scientific mind is one that relies on a lack of preconception and bias towards any idea. But anyone who has worked in science knows that this is false. A scientist without preconceptions, who does not listen to intuitions based on experience, is a horrible scientist. In fact, while the papers a scientist writes are important to the progress of science, it’s the ability of a scientist to make good judgments before the data exists that forms a lot of their value to the system.
Reading this book with COVID-19 raging, I couldn’t help but see that tension in how things have played out over the past two years. We came to a situation that was truly novel, at least as an instance, where there was no data early on and yet decisions had to be made. And these two visions of scientist value came into conflict. Why? Because of things like this — many scientists, asked “Will the vaccines provide at least a year of immunity?” said “We don’t really know.” (ADDED NOTE: here I am referring to immunity against severe disease). That’s a discourse rules answer that applies one model of a scientist’s value (rely on data) to a public issue. Alternatively, a scientist could say “Everything we know about both vaccines — of any type — and coronaviruses says, yeah, you’ll get a year out of it at least.” That’s another model of the value of scientists — that having seen many instances of things like what we were experiencing, at least in some dimensions, that they could make accurate guesses (at least about certain aspects of this, like the durability of immune responses). And while I know this is a controversial statement, I really do believe that a lot of people died unnecessarily and that institutional trust was eroded unnecessarily because many scientists selected on the wrong vision of value. When data is available, it’s discourse rules time (scientist with no presuppositions). But in the absence of data its the ability of scientists to make plausibility judgments that provides value.
Stepping back we see that this isn’t just a pattern for scientists, but rather for all professionals that must make public cases. The rules are not as strict, of course. But reporters and fact-checkers encounter similar patterns and tensions as scientists. From the discourse norms side of the equation, the fact-checker must take each Body Double charge as unique and specific. Like a scientist they can use their knowledge about how things generally go to make informed guesses as to where to look for answers. But the fact check itself is not a list of those intuitions; it is the result of the investigations, data-driven, spurred by those intuitions. And once the evidence is there, the ability to make this case, from the data itself, forms the value of reporting and fact-checking.
But what about when the data is not there? What about when we are in that pandemic situation where the answer is needed now and the data is going to take a while?
I’d argue that that is where we are with a lot of quickly emerging misinformation. Take the first example that we opened with, the “poll worker in Erie, PA “throwing away ballots”. I found this example on that day because, knowing there is a false claim or two like this every election I set up a process that looked for this term about every 20 minutes. That prediction paid off, and within about 10 minutes of it going up I had spotted it (around 11:23). Even then it was quickly accelerating. But it still had only moderate spread when I screencapped it, and at the time I came across it it was the only instance on Twitter.
It took me about five minutes to write up a report suggesting this was a likely hoax, and then promote it to Level 2, at 11:27:
Around the time I escalated it, about 15 minutes after the initial post, a number of other commentators reposted it using their own crop of it.
By the end of the hour, around noon my time, three things had happened. First, reporters and fact-checkers had confirmed there was no such worker in Erie, PA. Second, the initial Instagram post had been taken down. Third, one of the initial posts had been retweeted by Donald Trump Jr., and the whole thing had entered uncontrolled spread, as copies of copies of screenshots of Instagram posts circulated the net. And the reactions to this were, well, prescient.
Relevance to Mitigation Efforts
Now, I’m not arguing that content removal should happen on my (or anyone else’s) intuitions. In fact, I’m arguing the opposite. With the dynamics as they are, trying to speed up content removal is really a bit of a fool’s game, at least for certain types of content.
After all, this is an example of everything going right in a rapid response scenario. A piece of fakery so predictable that I set up a program to explicitly scan for it 10 days before it appeared, a discovery of it within minutes of it being posted, a report on it filed within minutes of finding it, an investigation of it which confirmed with folks in Erie that it was indeed fake, within 25 minutes of my report. And yet, none of it mattered.
One reaction — a wrong one — is that such content could be removed on a guess. That is, we know how this trope goes based on plausibility judgments of fact-checkers who have been in this rodeo dozens of times before, even though we don’t know the details of this instance. Is that enough to take it down? No, a thousand times no — that’s not a future anyone wants. Sometimes bad tropes turn out to be true. There’s a trope, for example, that emerges every time there is an explosion somewhere which claims that really it wasn’t an explosion, it was a missile. This trope has a history so bad it’s almost comical — conspiracy theorists would have you believe Flight TWA 800 didn’t explode, it was hit by a missile, the Pentagon wasn’t hit by a plane on 9/11, it was hit with a missile, the factory that recently exploded in Beruit didn’t explode it was hit by a missile, the RV in Nashville last Christmas, of which we have video from half a dozen directions and a crater under its smoking remains didn’t explode it was (you guessed it) hit by a missile.
But what about MH17, the flight that exploded over Ukraine, and was revealed pretty quickly to have been shot down — by a missile? Sometimes the trope proves true. Just as in this pandemic many times the past was a good guide for scientists to make guesses about how things would turn out — but sometimes the past wasn’t a great guide. So we want behavior that is informed by the sort of plausibility context a fact-checker calls to mind when seeing an instance of a trope, but we do not want summary judgments on that.
And here’s where we find perhaps one application of all this theory around a trope-focused approach. Because what if instead of focusing on truth or falsity of content early in a cycle we focused on providing the sort of trope-specific context fact-checkers bring to the table? We don’t have the fact-check yet — but we do have the history of the trope that informs their plausibility judgments. We know for example that this trope of the “ballot-discarding public official” will appear in 2022 and 2024, and that we’ll go through the same pattern of discovering it and taking so long to disconfirm it that any subsequent actions are rendered meaningless. But what if in the meantime you could ask everyone liking it and sharing it to read a short history of the trope, and the ways its been used in the past. If they still want to tweet it after knowing that hey, this is the same scam people fell for three elections in a row, then okay, go ahead.
You would have a set of tropes and subtrope pages, well-maintained that zeroed in not on broad truths but very specific subtropes that are typically associated with misinformation. You think Melania has been replaced by a body double because of a “height change”? OK, fine, but first look at a page that describes how that “the body double is a different height” played out with Paul McCartney, Hillary Clinton, and Avril Lavigne. When the fact-checking does not exist yet, provide the sort of context a fact-checker would start with.
Such an intervention is interesting to me because far from being an impingement on speech, correctly designed it’s a service. Perhaps I see a claim that “COVID-19 was actually a bioweapon” I want to retweet. As I go to do that, I am sent to a page that reminds me that while such a thing is possible the idea that everything from AIDS to Swine Flu was a bioweapon is pretty old, emerges like clockwork, and a lot of the arguments people make for the claim have been debunked in previous iterations. Does this look like some of those instances, or does it look substantially different?
To someone who just wants to put out the propaganda of course, this isn’t much of a deterrent. But to a user who is legitimately trying to process the issue, such context would be welcome. And if those users make better decisions about sharing it, the downward nudge in virality could be an important factor in a multi-prong approach against misinformation.
I also like, of course, that any attempt to spread something like a body double conspiracy or a claim that a debate participant was wired up with a secret headpiece will necessarily lead to a bunch of people learning about the history of the specific trope and perhaps being inoculated against false future instances of it.
I should say that I have been hesitant in the past nine months or so to suggest interventions at all. So many interventions designed to capture blatant mistruths seem to capture unwitting people of good will while the bad actors find ways to skate around them (or game the referees). And lots of good ideas are hampered by poor designs and non-existent support (e.g. Twitter’s ‘appeals’ process, which to all intents and purposes doesn’t actually exist).
But providing end-users “plausibility contexts” around specific (and very granular) tropes seems a much more promising approach than generic and useless “Go to the CDC”-type labels, and potentially much more responsive to emerging misinformation than claim fact-checking and content removal schemes. But it’s going to start with us moving away from larger, ideology bound narratives on the one hand and away from overly specific but slow-to-verify claims on the other. It’s this middle layer in-between the narrative and the claim — the trope — that is both specific enough that is can be targeted and predictable enough that interventions can finally get a step ahead of the game.
OK, that’s it for today — the final installment of this (Part #4) is next and will talk about using pre-bunking around tropes to reduce misinformation around events associated with those tropes.
People have a lot of stuff they can share or attend to online.
In order to efficiently create and process content we look at things like “evidence” through tropes
Tropes, not narratives or individual claims, are the lynchpin of activism and propaganda, whether true or false, participatory or not. They are more persistent than claims, more compelling than narrative.
The success of a given trope is often based on its “fit” with the media, events, and data around the event (the “field”). A trope must be compelling but also fit the media available to creators. In participatory propaganda (term from Wanless and Berk) tropes must be productive.
In participatory work, productive tropes are often adopted based on their productivity, and then retconned to a narrative. Narrative-claim fit is far less important than trope-field fit.
Today I want to show how tropes transcend narratives. A good trope that matches a field well will be used in many different contexts.
Over the next week I’ll go through some examples of tropes and the media environments in which they thrive. Most of these tropes are associated with misinformation, even if the trope does fit reality in many circumstances. Let’s start with Body Count.
Trope: A hidden cause is behind the deaths of many seemingly unrelated people. This cause is usually being covered up by a political or corporate elite.
Field: Death reports, either current ones (as they occur) or historical ones.
There are many times when a string of deaths is both suspicious and likely related to a cause that is being covered up. W.R. Grace hid evidence for years that its mine operations in Libby, Montana were linked to a string of deaths and illness in the area. It is well-documented that reporters that have challenged Vladimir Putin have often met untimely deaths. In the Philippines, it is widely believed that a series of assassinations of drug dealers are secret extrajudicial killings linked to the Duterte government.
It sometimes takes time to work out that many deaths have a single cause, and those making such claims are sometimes doubted. We rely on careful reporting to find and document these connections, and any good reporter will take such emerging patterns seriously. In those cases the trope can be used for good.
This post, however, is not about those cases. It is about the use of it for the Body Count trope for propaganda.
In the hands of a propagandist, the way the Body Count trope works in propaganda is this:
Pick your villain
As deaths are reported (your field) try to either find, imply, or manufacture a connection to the chosen villain.
Aggregate the deaths, and with each new instance, claim that this is one in a growing body of deaths
When there is pushback on any one death, point to the size of the list (the “body count”) and point out that even if x% of these were true it would be devastating
Body Count works well on two dimensions simultaneously: each new death is a “potential” connection which “eventifies” your claim and grabs attention. But the point is not the individual claim, but the “count” — the impression that there is a steady stream of suspicious deaths of such a volume that something is fishy here.
Clinton Body Count
A classic instance of Body Count trope is the “Clinton Body Count” claim, that hundreds of people who have “crossed” the Clintons and died early deaths have in fact been assassinated, no matter what the actually cause of death was. While there were many drivers of the Clinton Body Count claim, the count was advanced in the early 1990s by far-right activist Linda Thompson. Her initial list from 1993 was built on over time by others, and goes on to this day. The rules to the use of this trope were pretty simple — start by finding a death in Arkansas, Washington D.C., the Democratic Party organization, or in the military. Then find the connection:
Were they a Clinton friend? Insinuate they may have been about to “come clean”
Were they a Clinton enemy? Insinuate the death may have been payback.
Did they not know the Clintons, but were at some event that the Clintons were at? Perhaps they had “seen” something.
Did they not know the Clintons, were at no events with the Clintons, but worked for the Democratic Party? Maybe they found some paperwork, or hidden financial information.
And so on. Notice that the narrative here doesn’t play much of a role at all. You just take a death off the stack of recent or historical deaths, and find a connection. Part of what makes this work, as noted by Snopes, is that politicians are connected to a massive number of people compared to ordinary people, so connections are easy to find. And that’s the nature of the “field” — you can expect a nontrivial steady stream of deaths of people that are “associated” with the Clintons to occur as a matter of course. You keep an eye on deaths and see if you can make them fit. Even as I was putting this essay together today, another Clinton Body Count item came in:
The trope here is established enough that I don’t think it required any real effort on the part of people that pulled this death into the trope. Note too that the trope is so established that those sharing it have to do only minimal work to fit the event to the trope. “Found dead, being investigated” next to a Clinton connection is enough for it to trigger processing through the Body Count trope in its readership and encourage them to share. (One reason why any moderation effort is pretty futile — after a while a trope/field connection is so set that it barely needs signaling).
This example shows another key to the Body Count trope: jump in quickly, and point to the lack of knowledge of the cause of death in the immediate aftermath. It’s currently being investigated, as suicides are, but assuming it turns out to be a suicide expect scare quotes to appear around “ruled” a suicide.
Also note that there is really no narrative here, except only in the fuzziest sense. What was the purpose of this supposed killing? Revenge? Apart from the insanity of the premise, there are likely thousands of reporters who have broken stories about the Clintons. Why are they alive? Why would they risk it? Why would they care at this point? How could they pull it off? Why, if they did do it, would they decide to make it look like a suicide? This is an instance of what Rosenblum and Muirhead call “bare assertion”, a “conspiracy theory without the theory”. And it doesn’t need the theory, really, because it has the trope.
Notice too that any death can be made a relevant death in the Body Count trope. This one is a suicide, but the Clinton Body Count has included car crashes, plane malfunctions (“suspicious”), deaths by heart attack of heavy smokers (always death by an “apparent” heart attack), combat deaths, etc. Often there’s the invocation of some characteristic which would supposedly make the death unlikely — they were “thought to be in good health” before the heart attack, they crashed their plane “despite logging many miles as a pilot”, they were “killed in a robbery, but nothing was taken.” Going unnoted is that no-one predicts their own heart attack, that people who log a lot of flying miles increase their chances of dying in a plane crash, not reduce them, and that very often robberies go wrong.
In fact, these different elements become subtropes of the Body Count trope. That “killed in a robbery, but nothing was taken” piece? If you’re hip to trends in 2016 misinformation you might think I am referring to the 2016 death of Seth Rich. I am, in a way. This was supposedly the reason his death was “suspicious” to conspiracy theorists. But note that the subtrope of “killed in a robbery where nothing was taken” was part of Clinton Body Count accusations — in 1998:
Tropes link to other tropes in a fluid way. You keep an eye out for a death that might fight the Body Count trope. Once you find one, then the Body Count trope, in the ways you’ve seen it used, suggests was to juice the claim. Was it a robbery (“supposedly”)? Does it fit the “but nothing was stolen” trope? Use that. So some things were stolen? Ok, was it a “normally peaceful area”? All of these things are easily explainable, of course. For instance, in robberies that go “right”, it is very odd for robbers to leave money. But in robberies that go wrong (which includes most robberies where someone gets shot) that isn’t always the case, since the robbers often high-tail it for fear people heard the shooting. But the point here is not the answers, the point is that the “questions” raised are nearly as automatic as the trope itself. The suicide I mention here? Expect disinformers to go down the list of claims about the Vince Foster suicide in 1993 or any other Body Count death and see what fits.
Did they declare it a suicide quickly? Why wasn’t a real investigation done?
Did they declare it a suicide only after a long investigation? If it was so obviously a suicide, why did the investigation take so long?
Is there any way the death can be said to be unexpected? (Ignore that most suicides are unexpected)
Is there any plan that he made that was scheduled for after the suicide? (Ignore that most suicides are impulsive)
And so on. Again, narratives matter to the people producing, sharing, and consuming these, at least somewhat. It’s the Clinton Body Count, not the Paris Hilton Body Count (even though the techniques could be as easily applied there). But integration with the narrative does not drive the construction of these much. In fact, once the trope is set, the whole process works on something more resembling auto-pilot than directed creation, at least for the people that aren’t into meta-conspiracies like QAnon (more on tropes and meta-conspiracies in a future post).
Vaccine Body Count
Here’s the thing — all the same tactics used by the Clinton Body Count people? They’ve been used by anti-vaccine activists for years as well.
I’ll leave the historical tracing of these techniques to people better versed in the history than I. But consider the current vaccine-driven Body Count game being played, and how it matches almost beat-for-beat political Body Count games:
A high profile death occurs, for example the death of Marvin Hagler (or a near death like Christian Eriksen)
Anti-vaccine activists rush into the breach and scour social media for indication that person was vaccinated, or alternatively, just claim they were (which given most American adults are, would not be surprising).
They then take the “purported” cause of death an link it to a “known side effect” of the vaccine, or insist that the “alleged” cause of death can’t be right because the person was thought to be very healthy.
The “unexpected” nature of it is everywhere highlighted, where “unexpected” is used to imply suspicious. The fact that it is generally the case that deaths covered by the news are in general unexpected is ignored.
If the death just happened, they claim “doctors are looking into a suspicious death”. When doctors reach conclusions and those don’t link to vaccines, then say it was a cover up, and ask why they investigation took so long if it was so simple. If the investigation is short, they ask why it was so short — was it in fact covered up? Why was it never investigated?
If the doctors don’t reach their favored conclusion, they look for comments from family that disagree with doctors. If family doesn’t reach their conclusion, they find quotes from friends. If family wondered if at first it was due to vaccines, but now believe it wasn’t, they claim a cover up. If family change their mind the other way, of course, it’s evidence.
None of this requires narrative making or even much deep thought. And it’s almost bizarre how it’s the exactly the same method as the Clinton Body Count despite being from vastly different narratives. Let’s just think about Seth Rich or Vince Foster and replace “doctors” in those final bullets with “police”:
If the death just happened, they claim “police are looking into a suspicious death”. When police reach conclusions and those don’t link to foul play, then say it was a cover up, and ask why they investigation took so long if it was so simple. If the investigation is short, they ask why it was so short — was it in fact covered up? Why was it never investigated?
If the police don’t reach their favored conclusion, they look for comments from family that disagree with the police. If family doesn’t reach their conclusion, they find quotes from friends. If family wondered if at first it was suspicious, but now believe it wasn’t, they claim a cover up. If family change their mind the other way, of course, it’s evidence.
And so on. But what’s going on here is determined by the possibilities of the “field”, in both cases the steady stream of expected events that can be fit to the trope. And the process of finding them becomes so automatic that just we get into bizarre situations where Twitter has to run a trend like this, every time an unexpected death or near death occurs:
Non-obvious harms of the Body Count trope
Finally, it’s worth noting that aside from the obvious harms of spreading misinformation, this sort of activity pollutes the information space and may make it harder for people to assess real harms. As an example, it is the case that the CDC is looking into a slightly higher than expected incidence of myocarditis in teens who have been vaccinated. It’s extremely rare, but it warrants more investigation.
One could imagine a world of ethical activists, who use the power of the Body Count trope for good. Such activists would not work from the “field backward” — finding any death and connecting it, no matter how spuriously — but from the cause forward — highlighting exactly the cases that seem to be involved, and perhaps even calling attention to attributes that might link them. Indeed, such activity, while it may annoy the medical establishment, has called attention to disorders, diseases, and effects of chemical exposure that historically needed addressing. Tropes can be powerful tools in that way.
And I shouldn’t say “imagine”. These activists are out there. But as I’ve mentioned a number of times — the process is so automatic I’m not even sure it’s activism at the wheel in many cases. There’s the field, coming in, and there’s the toolbox of tropes to process it, categorize it, frame it, and amplify it. A man collapses on the field or commits suicide, 30 seconds later the Body Count trope is applied. Good signal is lost in a sea of ridiculous noise.
Note: In this post, I jump back and forth between the use of tropes to frame events ethically, non-ethically, and in-between. This is not meant to be “both-sidesim”. Rather it is meant to demonstrate something of the utmost importance to policy discussions about misinformation: there isn’t really a magical set of techniques associated with “misinformation” that can be discouraged, dampened, or banned. Rather, a group of people that range from ethical activists to snake oil salesmen to political motivated disinformers all use a toolbox largely shaped by the possibilities of the medium, and frame messages sent through it to work with its strengths and exploit its weaknesses.
I’m watching TV with my partner, and, in the show we’re watching, a member of a gang has said he wants to quit. He’s married now, you see. New lease on life. That’s fine, says the gang’s boss, no problem at all, let’s go for a ride back to headquarters and talk about it.
As the ride progresses, it’s clear they aren’t going to headquarters. Streets get less familiar, and the family man gets nervous. In fact, the car ends up turning off into an abandoned quarry, completely deserted. The character is told to step out and to kneel: he’s betrayed the gang. Pleads for his life. Dramatic music as the gang leader raises the gun and squeezes…
“Gun’s empty,” I say to Nicole.
“Of course,” she says back.
Click. The gun’s empty. Family man exhales in relief.
Now here’s a question — what show were we watching?
If you’re an avid consumer of TV thrillers the answer to that question is likely that it would be near impossible to narrow it down to one. Each of these elements is in hundreds of films and TV episodes:
The new family man wanting to retire from a life of crime (or spying, or terrorism), but not allowed to leave the organization
The ride where the rider realizes “Wait a second, this isn’t the way to X”
The deserted quarry, warehouse, or forest where a character pleads for his life
The assassination that turns out to be a scare tactic
The empty gun
These elements are so common that even in combination it can be a bit difficult to say what show we were watching. And once you get into combinations that aren’t exactly that sequence, you’re talking hundreds of shows.
These reusable blocks aren’t narratives. They are ready-to-use building blocks for any narrative of a suitably matching genre. They are commonly known as “tropes” and they are an important key to the understanding of participatory propaganda.
Enter the Trope
The word “trope” can mean an awful lot of things. The word itself just means something commonplace, available for reuse. Rhetoricians can be protective of the word, often seeing it as a synonym for a figure of speech. In cultural studies, “trope” often refers to repeated patterns of depiction in literature or film, particularly those that are socially harmful — the “trope” of the devious bisexual, for example, or the trope of the “white savior”. But common parlance in recent years has used trope in a related way popularized by the site TVTropes: a reused “narrative device or convention used in storytelling or production of a creative work.”
Tropes serve two purposes. The first is obvious, hopefully: they allow more efficient construction of narrative. A writer, looking to put together a compelling scene, has a toolbox of things proven to work. That scene where the character realizes while in the car “Wait a second, this isn’t the way to (wherever they thought they were going)!” — that scene works, it’s been tested before. It has the nice impact of a growing realization of the character (and a perhaps an earlier realization of the audience). It gets reused because it has proven itself. In this way, it functions like a narrative Pattern Language, a design approach that has been used in everything from software, to architecture, to pedagogy.
But tropes serve another purpose as well — they are a shorthand for the audience. As Steven Johnson noted in 2005, TV got much, much more complex from the 1950s to the 2000s (and has gotten even more complex since). Even a simplistic TV plot is asking viewers to weaves multiple intersecting narratives and different timelines together in ways a 1970s viewer would find overwhelming. Nowadays, a scene that would have been five or six lines of dialogue 30 or even 10 years ago is reduced down to three or four seconds of camerawork and a head motion. Plots are dense.
Johnson attributes our collective ability to consume more complex entertainment to an increase in willingness of viewers to engage in viewing that involves more cognitive load, but that’s not quite right. As the story of Nicole and me shows, we’re not exactly cognitively overloaded — even though the show we were watching, the solid but unremarkable Swedish thriller Blue Eyes — is many times more complex than the most demanding 1970s espionage film. What’s going on, mostly, is that TV shows can build more complex plots because a shorthand of tropes (as well as the comprehension of other bits of filmic grammar) has developed over time. That shorthand reduces cognitive load for the viewer, allowing for more complexity. A character that has just committed a betrayal gets picked up, looks out the window of the car and furrows their brow. They don’t even need to say “Hey where are we going?” The viewer knows what’s up, and can look for deviations or variations from the expected path. (This is not simply a progression for television — other art forms over time develop such tropes and moves towards more efficient and complex storytelling).
Tropes can be simpler as well (and some of the ones that we’ll talk about in a minute are quite simple). That scene where the detective says — hold on a second, rewind the video, and ENHANCE. Plot problems are solved with tropes that have a proven history of drawing in the viewer — “Here’s the weird thing, detective, the gun we found? It was loaded with blanks…” When they become overused (e.g. “The call is coming from inside the house!”) they become clichés and cease to be effective, but in the time between their first introduction and their relegation to the cliché graveyard they live a long productive life, both in direct reuse and the permutations they spawn.
Digital Activism and Tropes
In the past few years, researchers have given increasing attention to the relationship between elite framing of various issues and the broad participation of a non-elite, digitally networked population in producing and disseminating evidence for those frames (see Wanless & Berk’s work on Participatory Propaganda, for instance, as well as Asmolov). These patterns are not confined to “bad actors”, but are generally patterns around how people advance themes and narratives they find desirable. Some of what’s below is my own particularly trope-focused take, but some of these general patterns are also identified in An Xiao Mina’s excellent From Memes to Movements.
First, lets start with a simple trope that was not generally used to spread misinformation, but will demonstrate the dynamics at play here, which are common to all distributed networked activism and propaganda. (Importantly, I am using propaganda as a neutral term here). Back in 2019, a white woman named Jennifer Schulte called 911 on a Black family using a grill in a park, purportedly because they were in the wrong section of the park for grilling. A woman observing this, Michelle Snider, confronted her about the inherent racism of her use of an emergency number to deal with this minor park policy infringement, while filming her reaction. Over the course of the video the situation escalates, mostly due to the actions of Schulte, and her answers sound increasingly bizarre — she’s really calling 911, after all, because there have been lawsuits about safety of wrongly disposed charcoal. That’s her concern, that’s why she is harassing these Black people. By the time the police arrive, its Schulte who is in tears, claiming she was the person harassed, the true victim.
BBQ Becky, as she was named, became a meme, photoshopped into a million places, portrayed in a skit on Saturday Night Live. For many Black people, she was just one example of the way that white people use the force of the state to control and threaten Black folks, for whom police interactions carry disproportionate risks of jailing, injury, or death. The video itself supported a complex narrative of how systemic racism works, where white people treat the police force as their own security guards to support goals which are about white dominance and control of purportedly public spaces. It was, in its way, evidence supporting this narrative.
People don’t remember this, but the full video of that interaction? It’s 25 minutes long. The situation is undeniably a result of racism, and legitimately dangerous to the family she is reporting, but the video itself is messy, with a good deal of it being about a business card that Schulte refused to give back to Snider. In the longer video, Snider needles Schulte, and becomes a participant in the drama. But as it pinged around Twitter and elsewhere, both as a “discourse” and a “meme” the essential outline of it became clearer — a white woman, calling the police for a minor perceived infringement in a public space, acting as if this is the most normal thing in the world. And thus the larger trope was born.
Very quickly other incidents followed. A month later, a woman is caught on video phoning police on an eight-year old girl for selling water in front of her own apartment without a permit. Notably, this video is shorter — just 15 seconds, and references the #BBQBecky meme by calling the police caller #PermitPatty. It goes viral, and what had been a singular meme is now a deeper character trope, which explicates a chosen narrative concisely. (Again, I do not use narrative pejoratively here). Others follow: Golfcart Gail, Pool Patrol Paula. Some differ in the dynamics, or the actions, but they all follow the basic pattern.
We can see this process as just another level of memetic production and evolution, but I find the concept of tropes more helpful to me personally. This pattern has a character trope, combined with a specific, repeated scene trope. And one one level, the dynamics of this are far older than the web. Tropes have been helping storytellers tell stories since before recorded history.
The first way such tropes help is with selection. It is simply the case that Black Americans suffer many adverse impacts of racism in a given day or week, many of which could be filmed or shared. But as with a screenwriter choosing from many possible scenes to advance a narrative, it is not immediately apparent what sort of events are compelling to an outside audience. Tropes are tested, and proven to be compelling in ways that non-trope media is not. There’s a recipe that works, at least until it gets old. Tropes, in this way, help us spot compelling scenes, locations, characters that we might otherwise consider ordinary (if unjust).
Perhaps more importantly, as a trope becomes legible to an audience, the audience becomes better at both comprehending content associated with the trope, and understanding what content is likely to do well with the followers they share it with. While I do not have the data to prove this, my experience has been that when a new trope emerges, the first instance of that trope meanders a bit through the network. Often, as with BBQ Becky, there’s a “discourse” as to What It Really Means. Subsequent instances are often more concise and move through the network quickly. People know what it is, know what it means, often with only a glance.
Tropes also have deleterious effects, even when used to illustrate real and pressing events. By turning everything to a quickly understandable shorthand, they aid in comprehension but at the cost of flattening experience. I’m not the one to judge, of course, but to my eyes an Amy Cooper, calling 911 in Central Park and talking with distress about a Black man threatening her, is something much more sinister than a BBQ Becky. Run through the trope, however, she risks simply being another of a series of equivalent scenes. At the same time I would predict that had a largely white Twitter audience not been exposed to the trope of BBQ Becky and its kin that they may not have been able to even process the Amy Cooper video as an instance of something systemic and dangerous at all.
It’s important to note as well that while instances of a trope must align with a given narrative in order to be attractive to core audiences, tropes are not necessarily bound to a narrative or ideology. And for the most part they don’t gain their power (as tropes) from the narrative.
Turning Narratives and Themes into Scenes
So far we have sketched out a basic narrative construction box. Up top, there is a narrative. In a film this is the larger plot, the often summarized by the so-called logline. Logline of a relatively famous film: “When an optimistic farm boy discovers that he has powers, he teams up with other rebel fighters to liberate the galaxy from the sinister forces of the Empire.” (Star Wars, obviously). Narratives in propaganda and activism don’t work quite like this, but with some modifications they do: “A shadowy elite pushes suspicious drugs and various lockdown measures during a pandemic as a first step toward world totalitarianism”. Some traditions of cultural studies use the term narrative more broadly, but in literary studies narratives usually involve a certain set of antagonists or protagonists moving toward a goal.
More vague is the “theme”, and it’s often what people are talking about when they talk about narratives. A theme is often a general statement about how the world works, at least part of the time, but there’s no end goal to it. “Hard work pays off” is a theme. “The world is controlled by a shadowy network of corporate elites” is a theme. On the other hand, “Trump is attempting to overturn the election” or “Vaccines are really a plan to implement a totalitarian government” are, to my eyes, narratives. The represent not general statements on “the way the world works” but fuzzy claims about something that is happening.
It may be this distinction is too precious by half. The important thing is this — social movements have narratives and themes but social media is propelled by events. Something happened, something was discovered, something was discovered to have happened. Something is happening. Events are so much the currency of social media that if you want to convey an established fact on Twitter or Reddit, you’re likely to present the fact as an event, prefacing it with something along the lines of “I was today years old when I realized that…” You turn something old into a new event by framing it a discovery. If you want to discuss a general pattern of things, you’re likely to begin by hooking that analysis to a recent event. Occasionally someone gets away with something without eventifying it — “Some notes on the McCartney/Lennon partnership and what it can tell us about distributed wiki collaboration.” But even there we both know that it will do much better if it begins “On the occasion Paul McCartney’s birthday, some notes…”
This is not a new phenomenon, nor a particularly internet one. As far back as 1961, the American scholar Daniel J. Boorstin noted the rise of pseudo-events in response to an ever-hungrier news cycle. According to Boorstin, since the media spotlight almost exclusively privileges events, marketers found ways to gain the spotlight by creating events designed to convey what they wished to convey (or even to just get a piece of the viewer’s attention). Think about the yearly Apple product launch event, for example. The event consists of revealing a bunch of product information that could be uploaded to a website, or features you could discover next time you walk into an Apple Store, at the point you’re ready to purchase something new. In fact, there isn’t actually a reason for Apple to work on a yearly release cycle across all products. There’s no reason that an iPhone should be on a 12 month release cycle and unveiled the same day as a new activity monitor or exercise app or new chip spec in an upcoming MacBook. But the conversion of product changes and updates to compelling events is a large part of what drives Apple’s success. People talk about the genius of Steve Jobs as a designer, and maybe that’s true. But there are a lot of great designers. Jobs’s true genius — and what he is most remembered for, if people are being honest — is the way he understood that products had to be designed with an eye towards this sort of eventification. Designers had always balanced user needs with the needs conveyed by a sales force around what they needed to sell a product. Jobs understood that in an age of scarce attention products had to be designed with an eye towards the compelling events they could create. (Rule 1: delete ports 18 months before it is really viable to create an impassioned, media-consuming public debate about whether you deleted the ports too soon).
Boorstin’s analysis didn’t stop at marketing. In fact, he critiques a lot of the events that have become sacrosanct political traditions. Press conferences, presidential debates, and even interviews are generally inefficient ways to communicate policy, yet part of a larger trend dating back to the adoption, in Boorstin’s view, of a 19th century telegraph-influenced model of news production. In a world obsessed with providing the most up-to-date news, non-events must be framed as events. As news cycles became tighter and more visually driven, the process, in Boorstin’s view, accelerated.
While Boorstin was particularly interested in the idea that psuedo-events were planned, with an eye towards how they might capture the media spotlight, such critiques were expanded by scholars such as Neil Postman, who advanced a more general theory of the impact of the fascination with novelty on news production and consumption. Again, in the interest of not turning this essay into a small book we’ll move on — the point here is that these are long noted trends: as communication technology has increasingly favored and privileged currency ideas, products, claims, and social issues must be framed as discrete events in order to be disseminated more broadly, at least in comparison to an earlier culture. (One may of course argue that currency has always been a staple of orality, but, again, moving on…)
When it comes to social media, this means that activists must convert the narratives and themes they care about into a series of events if they are to be disseminated and have impact. There are a couple different modes for this. The most obvious is what we saw with BBQ Becky and the videos that followed. In that case a series of events illustrating broader themes and specific narratives were captured and amplified. Notably, once it was clear that such events were compelling and aligned with a desired narrative such events were both captured and amplified regularly.
And this is why tropes are so fundamental to the understanding of persuasion, propaganda, and activism online. Tropes are the mechanism through which we reliably convert narratives and themes into scenes.
I use scenes as a term instead of events, because it captures for me the full range of elements which are attended to in these videos, though I don’t mean to indicate that tropes only produce scenes. But here the term is helpful. Like our “empty gun in the abandoned quarry” story that began this, there’s a character, there’s a location, there’s an action. One of the powers of thinking in tropes is that certain combinations are found to work. The “Karen”, for example, is a character trope recognizable at the core of most of the BBQ Becky type videos. It pairs with this plot trope around the policing of public spaces. The phone call is an optional but desirable element. The nature of the public location works well with the character trope — the impact here is partly the disparity between the either genuine or performed distress of the “Karen” and the way those in the surrounding location is just trying to get on with its day. None of these things are required, of course, but to the extent they are there, both creators and viewers intuitively sense the value of them to the event.
This isn’t just a theory. One of the fascinating moments in the trope I’ll call here the “Karen Police” is occurs in October 2018, six months after the trope was established. A woman falsely accuses a young Black boy of groping her. Unlike the the BBQ Becky video that launched this trope, the woman is not questioned or pursued. She’s filmed making what would later turn out to be a fake call to the police, and the creator alternates between filming the calm crowd looking at her like “WTF, lady?”, the upset boy, and her over-the-top performance of victimhood. It’s cleanly done in all the ways the initial BBQ Becky video was not. But the kicker is this — while she is still on the phone you hear a man’s voice on the video from behind the camera. It’s not clear to me if it is the person filming or someone next to them, but they are close.
“Cornerstore Caroline”, he pronounces.
Again, I don’t mean downplay the real and upsetting elements of the video. But life in the U.S. for Black Americans has many upsetting elements and incidents, not all of which are captured or shared. What is interesting to me here is that, even in the middle of this, the people capturing this are capturing it as the trope. They are fully aware of the value of what they are capturing here, and its likely trajectory across the internet. Now established, the trope indicates what content to capture, the framing to share it under, and makes it less cognitively demanding for an audience to process and disseminate.
In participatory propaganda, tropes solve a specific problem for creators. Scenes — whether captured video, a news article plus framing, or a claimed discovery of “something fishy in the data” are often captured from some larger store of experience, existing media, data, news stories, or larger events. But there’s an awful lot to choose from.
In 2020, for example, the overriding narrative of the Trump campaign was clear from early on: the Democrats were using a variety of coordinated efforts to “steal” the election. Somewhat differently from 2016, this false narrative was interwoven with themes that a “Deep State” government, largely captured by Democrats, was a key force in undermining Trump’s success. The “steal”, from early on, was not the actions of individual illegal voters (as claimed in 2016), but of a vast conspiracy of government officials.
There was already an existing trope that fit this narrative. The trope “ballots discarded/ballots found” focuses on purported discovery (event!) of ballots either not counted, or the appearance of mysterious ballots late in the vote-counting that put an opponent over the top at the last minute. The trope is associated with certain scene locations to make it more compelling. In the 2008 Coleman/Franken contest it was “mysterious box of ballots found in the trunk of a car”. In 2016, it was “boxes of fake ballots” found in a warehouse supporting Clinton. In 2018, in a Florida race it was a box of ballots found behind a school after polling closed, and also in the back of an Avis rental car at the airport.In Massachusetts primary race, it was a box of ballots found in a maintenance closet.
The trope is useful in a number of ways. First, it turns a claim into an event quite nicely. There’s a full scene here — someone discovers a mysterious box in a dodgy location. Second, as seen above, it can fuel a range of media. It can direct the production of fake stories (as the one above) but more importantly it can be used to frame innocuous incidents as something more sinister. Very often the deception is in immediately jumping on the “box of ballots found” story when it is found, but before its contents are inspected. The procedures involved when a potential box of votes is found move forward at a rate less than internet speed. The box must be secured, and not opened until the correct people can be present to inspect it. In the case of the Florida ballots supposedly in a rental car and behind a school, for example, after quite a bit of generated outrage over the incidents it turned out the boxes contained polling supplies, but no ballots (in many districts it is common procedure to reuse the box that is used to ship blank provisional ballots to a polling location to load up supplies at the end of the night, precisely because the remaining provisional ballots are counted, secured and transported from the site under a different process).
But what makes the trope really work here is the range of media and events that can be used to create scenes. Take the above picture, used in the fake story about Clinton. The man that created the story explains his process:
A photograph, he thought, would help erase doubts about his yarn. With a quick Google image search for “ballot boxes,” he landed on a shot of a balding fellow standing behind black plastic boxes that helpfully had “Ballot Box” labels.
It was a photo from The Birmingham Mail, showing a British election 3,700 miles from Columbus — but no matter. In the caption, the balding Briton got a new name: “Mr. Prince, shown here, poses with his find, as election officials investigate.”
There’s lots of pictures of things that are ballots or can be portrayed as ballots online, a Google search away.
Even better is this — after any election you are guaranteed to find some instances of boxes discovered that are associated with polling places. There is a guaranteed stream of events you can use to create this sort of scene after every election, you just need to keep an eye out in the news, and be quick with the sharing, before they open that box and find that it has nothing to do with ballots. This is similar to the “Karen Police” trope — there is a guaranteed stream of events of white women calling the police that will be available for framing, once you know the trope and keep your eye out for it.
I call this pattern “trope-field fit” and believe it is a crucial part of participatory propaganda. A trope has to produce compelling events, of course, whether real or fake. It should align, at least marginally, with the narrative or themes you want to advance. But if you really want it to be participatory, it needs to be a trope that can pull from a known store of events, media, news stories, or the like. The trope and the media to search have to be a good pairing, with the trope telling activists what to look for, and the field providing enough examples that can be turned to that purpose that searching is not in vain.
This isn’t to say that a single event can’t serve a propaganda function, of course. Tropes are powerful, even if not participatory. One interesting parallel to the Karen Police videos came from the right-wing in 2015. At a University of Missouri protest on racial discrimination, a liberal faculty member was filmed telling a student journalist that they couldn’t film the protest, that they needed to leave. She then asks if she can get some “muscle” to remove him.
I’m not here to debate the incident or the larger question of filming and protests. Let’s just say, however, I’m not a fan of this woman while at the same time aware the larger narrative around this video had many problems.
But it’s remarkable to me the similarities in the structure here to the Karen Police videos. A person in a public place, one that they have a right to occupy, is approached and asked to leave by a seemingly hysterical woman, when he refuses, she calls for some “muscle”. It’s connected to a different narrative of course. The “muscle” piece of this is compelling to at least some viewers because it taps into longstanding racist narratives about a weak liberal elite maintaining power through the use of Black muscle to oppress “true” Americans. It’s aligned with a fundamentally different narrative. But structurally, it’s strikingly similar.
In keeping with the general power of this trope, on both the right and the left, the video was also a remarkably effective piece of propaganda (I use propaganda here in its non-judgmental sense of messages designed to create a sympathy with a given worldview). In many ways this video marks a shift in the focus of right-wing activism more generally in 2015, one which coincided with Trump’s rise to prominence. The issue of liberals as the real enemies of free speech here is centered, and higher education is rediscovered as a central villain. In the months after this video was replayed on Fox News in a near loop, Republican support for higher education plummeted, and many mainstream media outlets began to run columns on threats to free speech from the left. Protests, oddly, became seen as a suppression of free speech rather than an expression of it. I can’t pin all of that on this video, but there is some special sauce to it that most definitely aided in accelerating all of this. And part of it is due to how it takes various compelling tropes and creates a compelling scene.
For all its effectiveness, however, this was not the first in a long line of videos of liberal women attempting to remove reporters or those with opposing views from public spaces. And that’s not because people didn’t want more examples. It’s because there just isn’t a predictable stream of events like this. It’s lightning, striking once. You could tell people to keep an eye out for this, but the incidence is going to be so low that they really shouldn’t bother.
Perhaps there were a couple attempts to duplicate this success in the weeks that followed that I don’t remember. If there were, none of them stuck. Instead, it was the trope of the peaceful reporter attacked by “antifa”, a narrative that could draw from a more predictable (and often engineered) set of events that would eventually take root as the participatory propaganda trope of choice around these issues, supporting this nexus of themes. My view on this is that it is not that that trope was more compelling, but it was just a better fit for the sort of video that was generally captured at protests (the “field” of media to mine).
When Tropes Bend to the Field
As mentioned above, trope-field fit is crucial in participatory propaganda. You want compelling arrangement of tropes, but if you really want to supercharge community production of events/scenes around those tropes the trope has to work with a given field of media, data, or predictable stream of events.
Take the example of the “ballots discovered/ballots discarded” trope mentioned above. In the traditional version of it it’s a trope for after the election, when there is likely to be a number of stories about someone, somewhere finding a box of something. Before the election, on the other hand, it doesn’t get much use. You have to have the election before you can find “discarded” ballots. However, in 2020, a new version of this appeared — the discarded mail meme. Since mail-in ballots were in the news, every event where mail was found discarded could be portrayed as a “ballots discarded” instance, even if there were no ballots found. And if the field of current events proved to not supply enough examples, there was wealth of videos and news stories and photographs from the past 20 years showing all sorts of mail being dumped by postal carriers, media that could be reframed as current and election related.
It’s worth noting that with the exception of a weird event involving what appeared to be a postal worker keeping bags of mail at their home, almost none of these events had anything to do with the election. But the dense field of past media and current incidents combined with the discarded mail trope produced one of the more participatory propaganda efforts of the election, largely because the fit between trope and field was so solid.
If this seemed to end suddenly it’s because it did! I had to break up this writing into a few parts. Up next: Part 2 (on the durability and portability of tropes) and Part 3 on tropes and mitigation efforts.
Today’s activity revolves around a tweet that National Geographic (through the Society) has recognized a fifth ocean. I use this tweet here as a jumping off point, but if you want to run it in in another platform you can find examples anywhere.
Like over half the prompts we use with SIFT, this is a true prompt, and shows how SIFT works well. If you know the Today Show, you can INVESTIGATE the source through hovering and take into account the blue check, and that’s good to go. If you don’t trust the show or don’t know them, you could TRACE this back to the source, in this case National Geographic, and make sure this is a correct summary of what was said. If you’re just interested in this claim that there are five, not four, oceans, you can FIND better coverage and learn about the larger case for five oceans — which is not a new thing at all, even if the boundaries are under dispute.
I walk through the process here, beginning to end. Give it a play!
One thing I’ll point out here — when you do activities like this you introduce students to our current knowledge infrastructure. As shown in the video, they learn about NOAA, they learn about the IHO. And I can’t stress how important this is. Oftentimes the first time a student will hear about NOAA, for instance, is in the context of a divisive issue like climate change. Getting students familiar with various agencies and professional organizations, what they do well and what they do poorly, is important as students come to future debates where the nature of these agencies is often misrepresented.
We spend all this time asking “Why don’t people trust agency X on issue Y?” and sometimes there’s good reasons for that! But a lot of the time the question we should be asking is “Why should someone trust Agency X if the only time they ever hear about it is when it is mired in political controversy?” We spend so much time teaching students either facts or methods or concepts in a domain like science, and very little time introducing students to the knowledge producing organizations and social processes in those fields, which is arguably more important info to the average citizen.
I don’t go deeply into this in the video, but as your students click around through the search results on this task, you should get them to look up NOAA, by using the About this Result function in Google, but go the extra step and pull up the Wikipedia page. Talk about the various things that NOAA does, the role of these sorts of agencies in producing knowledge, the vast array of equipment and sensors. The data produced that even when not used by NOAA directly makes the work of many other scientists possible.
Then, maybe when your students do come across NOAA in a politicized context they’ll have some background. But if we don’t teach them, how would they know?
Welp, I was going to write a much more nuanced post about problems with the Twitter appeals process, but I’ll just put this here instead for now.
I got banned wrongly for a tweet last week where I was talking about the history of conspiracy theory and its relationship to current COVID-19 misinformation. Someone had posted that conspiracy pyramid that shows the relative harms of conspiracy and asked where fluoride might fit. I replied saying I thought that fluoride definitely belonged in the 5g layer — not anti-Semitic but definitely part of that dangerous John Birch Society politics/medical-conspiracy stew. A few minutes later I was hit by this.
Now, I want to be clear. This stuff happens to other people quite a bit, particularly women academics and activists, due to the gaming of reporting features by trolls. And it happens to lots of regular folks as well due to the algorithmic nature of enforcement — I saw someone go to Twitter jail once for tweeting “I hope Trump chokes on his own uvula” (incitement to violence!). So none of this is particularly noteworthy. This has been broken a long time, and there’s a lot of people I respect who say it may not even be fixable. I’m more optimistic and think it could be made workable, but even there it’s always going to be imperfect: there’s some collateral damage with even the best moderation regimes.
But in any case, I decided to opt for the appeal. After all, I’m a well-known expert on media literacy and COVID-19. My pinned tweet is actually a OneZero article on my efforts to fight misinformation on COVID-19, an effort I got involved in mid-February 2020, before Twitter was even thinking about this stuff. Etc, etc. I expected the appeal might take three days, maybe. So I appealed.
Now, appealing isn’t cost-free. In fact, one of the primary ways reporters contact me for information on how best to fight COVID-19 misinfo is through Twitter DMs, and when you decide to appeal you lose all access to your DMs, all ability to browse, everything. (And perversely, all those DMs just go into a bit of a black hole, there for when you get privileges back, but with no one DMing you knowing that in the meantime you can’t see them). Getting banned for alleged COVID misinfo significantly affects my ability to work on real COVID misinfo. On the other hand, I don’t want to start accruing a bunch of black marks that might get me banned sometime down the road.
Anyway — it’s been a week now. I’ve hesitated writing this because I actually support stronger moderation on Twitter and for the love of God, this isn’t a “I’ve been censored” story. But as always with policy, stronger isn’t enough, smarter means much more. And an appeals process that is in effect a week’s ban isn’t really an appeals process at all. It would make more sense to me, and everyone else, to simply give up the pretense of an appeals process on individual tweets altogether, until Twitter can actually run one effectively. Had they not offered one, I’d have treated this as an algorithmic goof I had to live with; instead I lost a week on Twitter which I would have been using to actually advance anti-misinformation practices.
So that would be my recommendation to Twitter. Either cancel the appeals process, apply it narrowly to suspensions, or speed it up. At the very least, inform people engaging in it what the average time for resolution is. And while my suspension probably won’t derail national or international efforts against COVID-19, I can’t help but think of all the medical researchers and public policy people out there using Twitter to communicate and collaborate. So as much as Twitter seems to think any deference to academic culture is a thumb on the scale, I really hope they can have someone write up a list of experts more important than me and take a bit more care before they ban them. I assume what I was hit with was based on a programmatic scan, not trolls gaming reporting. But the anti-vaccine trolls are out there and I know they are reporting the heck out of anyone that gets in their way. If Twitter doesn’t make a nominal effort to protect those researchers, there will be much more high-profile (and damaging) bannings to come.
(Incidentally the fact that the report does not actually tell me if I have been banned by a programmatic scan –having 5g and vaccines in the same tweet — or via a report is very bad in terms of both transparency and utility. I actually need to know whether it is a troll report or algorithm. If it’s an algorithm, it’s a lightning strike, and I go on the way I have. If the trolls have found me, that’s a different problem, and one I need to be alerted to.)
If the appeal doesn’t come through soon, I’ll remove the tweet, which I guess means I’ll see you all in about 12-24 hours. (UPDATE: I have removed the tweet and am back)
One final note — I also hesitated putting this up because I don’t want to field questions from reporters about it. So many women and people of color deal with this sort of issue constantly, due to targeting by trolls. Talk to them, not me. Maybe actually phone up a sex worker and learn about crazy path they have to thread on various platforms to avoid being shadowbanned, or social justice activists whose every sarcastic tweet is pored over and brigaded by trolls looking to get them kicked off the platform. Also, as I said, I’m broadly supportive of Twitter’s efforts to keep COVID misinfo off the platform. To paraphrase the famous Obama quote, I’m not against moderation, I’m against dumb moderation. But if you are a reporter looking to talk about moderation challenges, I highly suggest talking to people besides me. You can start with Sarah T. Roberts on what really goes on behind the scenes, and Safiya Noble on the issues of algorithmic enforcement (which again, are felt less by people like me than others). I find Siva Vaidhyanathan’s thesis that the system cannot actually be made to work a bit more pessimistic than my take, but one that deserves more airtime. And of course for general policy perspective on platforms, my colleague at the Center for an Informed Public, Ryan Calo, is always a good call.
Still banned from Twitter (over a dumb mistake their algorithm made), so I’ll just put this here — I am finding it really hard to figure out if some of these QAnon groups are really rifting at the moment over things not playing out as they were told or if the groups have been infiltrated by normies posing as disaffected QAnon supporters. I think honestly it’s a bit of both, I just don’t know the ratio.
If normie infiltration plays even a small role, that’s honestly fascinating. Infiltration not by radicals but by centrists. Strange times.
I have a couple people in my online social circle who were over the past month telling followers to “just watch” what would happen on the 6th, when everybody but them and their followers would be surprised that Joe Biden didn’t become president. At first, Mike Pence was going to heroically pull some imagined maneuver. Then it was another theory. But the idea from the posters was the same: remember who was right and who was wrong, they’d ask, when this all happens.
I don’t think they were expecting what happened to happen. But I think they were doing something that feels very much like clout-building: taking a gamble on being the one person who seemed in the know, because the rewards would be significant if true.
There’s talk right now about the number of social media influencers at the Capitol Insurrection. A lot of the people leading it were media stars, and it’s difficult to know how much of it they did for their brand, and how much was for the desired result.
But I’m not sure those dynamics stop at a certain floor of users. It seems to me that everyone has at least a few people in their online circles who are approaching issues around these events and conspiracies related to them as a brand-building process. In that case, can we really say the motivation is as simple as “confirmation bias”? Or would we be better off thinking of these dynamics around issues of personal brand-building, its incentives and disincentives?
Disinformation has always been about getting elites to do things. That’s the point that so many who have looked at what percentage of ppl saw what on Facebook have missed. The public isn’t a target — it’s a vector (and it’s not the only vector).
Hopefully, as we watch what’s going on today, people can see that now? We track spread, but the real measure is penetration into groups that either make decisions or exert broad public influence. Or exert influence over those with influence.
Whether it’s our President who is talking about “shredded votes” in Fulton County, the politicians frightened of a small but heavily deluded set of future primary voters, or health care workers starting to plug into antivax networks due to COVID, that’s what to watch.
And by that measure, I’m sorry to say, we’re looking increasingly fucked.