social sciences

study:-social-media-probably-can’t-be-fixed

Study: Social media probably can’t be fixed


“The [structural] mechanism producing these problematic outcomes is really robust and hard to resolve.”

Credit: Aurich Lawson | Getty Images

Credit: Aurich Lawson | Getty Images

It’s no secret that much of social media has become profoundly dysfunctional. Rather than bringing us together into one utopian public square and fostering a healthy exchange of ideas, these platforms too often create filter bubbles or echo chambers. A small number of high-profile users garner the lion’s share of attention and influence, and the algorithms designed to maximize engagement end up merely amplifying outrage and conflict, ensuring the dominance of the loudest and most extreme users—thereby increasing polarization even more.

Numerous platform-level intervention strategies have been proposed to combat these issues, but according to a preprint posted to the physics arXiv, none of them are likely to be effective. And it’s not the fault of much-hated algorithms, non-chronological feeds, or our human proclivity for seeking out negativity. Rather, the dynamics that give rise to all those negative outcomes are structurally embedded in the very architecture of social media. So we’re probably doomed to endless toxic feedback loops unless someone hits upon a brilliant fundamental redesign that manages to change those dynamics.

Co-authors Petter Törnberg and Maik Larooij of the University of Amsterdam wanted to learn more about the mechanisms that give rise to the worst aspects of social media: the partisan echo chambers, the concentration of influence among a small group of elite users (attention inequality), and the amplification of the most extreme divisive voices. So they combined standard agent-based modeling with large language models (LLMs), essentially creating little AI personas to simulate online social media behavior. “What we found is that we didn’t need to put any algorithms in, we didn’t need to massage the model,” Törnberg told Ars. “It just came out of the baseline model, all of these dynamics.”

They then tested six different intervention strategies social scientists have been proposed to counter those effects: switching to chronological or randomized feeds; inverting engagement-optimization algorithms to reduce the visibility of highly reposted sensational content; boosting the diversity of viewpoints to broaden users’ exposure to opposing political views; using “bridging algorithms” to elevate content that fosters mutual understanding rather than emotional provocation; hiding social statistics like reposts and follower accounts to reduce social influence cues; and removing biographies to limit exposure to identity-based signals.

The results were far from encouraging. Only some interventions showed modest improvements. None were able to fully disrupt the fundamental mechanisms producing the dysfunctional effects. In fact, some interventions actually made the problems worse. For example, chronological ordering had the strongest effect on reducing attention inequality, but there was a tradeoff: It also intensified the amplification of extreme content. Bridging algorithms significantly weakened the link between partisanship and engagement and modestly improved viewpoint diversity, but it also increased attention inequality. Boosting viewpoint diversity had no significant impact at all.

So is there any hope of finding effective intervention strategies to combat these problematic aspects of social media? Or should we nuke our social media accounts altogether and go live in caves? Ars caught up with Törnberg for an extended conversation to learn more about these troubling findings.

Ars Technica: What drove you to conduct this study?

Petter Törnberg: For the last 20 years or so, there has been a ton of research on how social media is reshaping politics in different ways, almost always using observational data. But in the last few years, there’s been a growing appetite for moving beyond just complaining about these things and trying to see how we can be a bit more constructive. Can we identify how to improve social media and create online spaces that are actually living up to those early promises of providing a public sphere where we can deliberate and debate politics in a constructive way?

The problem with using observational data is that it’s very hard to test counterfactuals to implement alternative solutions. So one kind of method that has existed in the field is agent-based simulations and social simulations: create a computer model of the system and then run experiments on that and test counterfactuals. It is useful for looking at the structure and emergence of network dynamics.

But at the same time, those models represent agents as simple rule followers or optimizers, and that doesn’t capture anything of the cultural world or politics or human behavior. I’ve always been of the controversial opinion that those things actually matter,  especially for online politics. We need to study both the structural dynamics of network formations and the patterns of cultural interaction.

Ars Technica: So you developed this hybrid model that combines LLMs with agent-based modeling.

Petter Törnberg: That’s the solution that we find to move beyond the problems of conventional agent-based modeling. Instead of having this simple rule of followers or optimizers, we use AI or LLMs. It’s not a perfect solution—there’s all kind of biases and limitations—but it does represent a step forward compared to a list of if/then rules. It does have something more of capturing human behavior in a more plausible way. We give them personas that we get from the American National Election Survey, which has very detailed questions about US voters and their hobbies and preferences. And then we turn that into a textual persona—your name is Bob, you’re from Massachusetts, and you like fishing—just to give them something to talk about and a little bit richer representation.

And then they see the random news of the day, and they can choose to post the news, read posts from other users, repost them, or they can choose to follow users. If they choose to follow users, they look at their previous messages, look at their user profile.

Our idea was to start with the minimal bare-bones model and then add things to try to see if we could reproduce these problematic consequences. But to our surprise, we actually didn’t have to add anything because these problematic consequences just came out of the bare bones model. This went against our expectations and also what I think the literature would say.

Ars Technica: I’m skeptical of AI in general, particularly in a research context, but there are very specific instances where it can be extremely useful. This strikes me as one of them, largely because your basic model proved to be so robust. You got the same dynamics without introducing anything extra.

Petter Törnberg: Yes. It’s been a big conversation in social science over the last two years or so. There’s a ton of interest in using LLMs for social simulation, but no one has really figured out for what or how it’s going to be helpful, or how we’re going to get past these problems of validity and so on. The kind of approach that we take in this paper is building on a tradition of complex systems thinking. We imagine very simple models of the human world and try to capture very fundamental mechanisms. It’s not really aiming to be realistic or a precise, complete model of human behavior.

I’ve been one of the more critical people of this method, to be honest. At the same time, it’s hard to imagine any other way of studying these kinds of dynamics where we have cultural and structural aspects feeding back into each other. But I still have to take the findings with a grain of salt and realize that these are models, and they’re capturing a kind of hypothetical world—a spherical cow in a vacuum. We can’t predict what someone is going to have for lunch on Tuesday, but we can capture broader mechanisms, and we can see how robust those mechanisms are. We can see whether they’re stable, unstable, which conditions they emerge in, and the general boundaries. And in this case, we found a mechanism that seems to be very robust, unfortunately.

Ars Technica: The dream was that social media would help revitalize the public sphere and support the kind of constructive political dialogue that your paper deems “vital to democratic life.” That largely hasn’t happened. What are the primary negative unexpected consequences that have emerged from social media platforms?

Petter Törnberg: First, you have echo chambers or filter bubbles. The risk of broad agreement is that if you want to have a functioning political conversation, functioning deliberation, you do need to do that across the partisan divide. If you’re only having a conversation with people who already agree with each other, that’s not enough. There’s debate on how widespread echo chambers are online, but it is quite established that there are a lot of spaces online that aren’t very constructive because there’s only people from one political side. So that’s one ingredient that you need. You need to have a diversity of opinion, a diversity of perspective.

The second one is that the deliberation needs to be among equals; people need to have more or less the same influence in the conversation. It can’t be completely controlled by a small, elite group of users. This is also something that people have pointed to on social media: It has a tendency of creating these influencers because attention attracts attention. And then you have a breakdown of conversation among equals.

The final one is what I call (based on Chris Bail’s book) the social media prism. The more extreme users tend to get more attention online. This is often discussed in relation to engagement algorithms, which tend to identify the type of content that most upsets us and then boost that content. I refer to it as a “trigger bubble” instead of the filter bubble. They’re trying to trigger us as a way of making us engage more so they can extract our data and keep our attention.

Ars Technica: Your conclusion is that there’s something within the structural dynamics of the network itself that’s to blame—something fundamental to the construction of social networks that makes these extremely difficult problems to solve.

Petter Törnberg: Exactly. It comes from the fact that we’re using these AI models to capture a richer representation of human behavior, which allows us to see something that wouldn’t really be possible using conventional agent-based modeling. There have been previous models looking at the growth of social networks on social media. People choose to retweet or not, and we know that action tends to be very reactive. We tend to be very emotional in that choice. And it tends to be a highly partisan and polarized type of action. You hit retweet when you see someone being angry about something, or doing something horrific, and then you share that. It’s well-known that this leads to toxic, more polarized content spreading more.

But what we find is that it’s not just that this content spreads; it also shapes the network structures that are formed. So there’s feedback between the effective emotional action of choosing to retweet something and the network structure that emerges. And then in turn, you have a network structure that feeds back what content you see, resulting in a toxic network. The definition of an online social network is that you have this kind of posting, reposting, and following dynamics. It’s quite fundamental to it. That alone seems to be enough to drive these negative outcomes.

Ars Technica: I was frankly surprised at the ineffectiveness of the various intervention strategies you tested. But it does seem to explain the Bluesky conundrum. Bluesky has no algorithm, for example, yet the same dynamics still seem to emerge. I think Bluesky’s founders genuinely want to avoid those dysfunctional issues, but they might not succeed, based on this paper. Why are such interventions so ineffective? 

Petter Törnberg: We’ve been discussing whether these things are due to the platforms doing evil things with algorithms or whether we as users are choosing that we want a bad environment. What we’re saying is that it doesn’t have to be either of those. This is often the unintended outcomes from interactions based on underlying rules. It’s not necessarily because the platforms are evil; it’s not necessarily because people want to be in toxic, horrible environments. It just follows from the structure that we’re providing.

We tested six different interventions. Google has been trying to make social media less toxic and recently released a newsfeed algorithm based on the content of the text. So that’s one example. We’re also trying to do more subtle interventions because often you can find a certain way of nudging the system so it switches over to healthier dynamics. Some of them have moderate or slightly positive effects on one of the attributes, but then they often have negative effects on another attribute, or they have no impact whatsoever.

I should say also that these are very extreme interventions in the sense that, if you depended on making money on your platform, you probably don’t want to implement them because it probably makes it really boring to use. It’s like showing the least influential users, the least retweeted messages on the platform. Even so, it doesn’t really make a difference in changing the basic outcomes. What we take from that is that the mechanism producing these problematic outcomes is really robust and hard to resolve given the basic structure of these platforms.

Ars Technica: So how might one go about building a successful social network that doesn’t have these problems? 

Petter Törnberg: There are several directions where you could imagine going, but there’s also the constraint of what is popular use. Think back to the early Internet, like ICQ. ICQ had this feature where you could just connect to a random person. I loved it when I was a kid. I would talk to random people all over the world. I was 12 in the countryside on a small island in Sweden, and I was talking to someone from Arizona, living a different life. I don’t know how successful that would be these days, the Internet having become a lot less innocent than it was.

For instance, we can focus on the question of inequality of attention, a very well-studied and robust feature of these networks. I personally thought we would be able to address it with our interventions, but attention draws attention, and this leads to a power law distribution, where 1 percent [of users] dominates the entire conversation. We know the conditions under which those power laws emerge. This is one of the main outcomes of social network dynamics: extreme inequality of attention.

But in social science, we always teach that everything is a normal distribution. The move from studying the conventional social world to studying the online social world means that you’re moving from these nice normal distributions to these horrible power law distributions. Those are the outcomes of having social networks where the probability of connecting to someone depends on how many previous connections they have. If we want to get rid of that, we probably have to move away from the social network model and have some kind of spatial model or group-based model that makes things a little bit more local, a little bit less globally interconnected.

Ars Technica: It sounds like you’d want to avoid those big influential nodes that play such a central role in a large, complex global network. 

Petter Törnberg: Exactly. I think that having those global networks and structures fundamentally undermines the possibility of the kind of conversations that political scientists and political theorists traditionally talked about when they were discussing in the public square. They were talking about social interaction in a coffee house or a tea house, or reading groups and so on. People thought the Internet was going to be precisely that. It’s very much not that. The dynamics are fundamentally different because of those structural differences. We shouldn’t expect to be able to get a coffee house deliberation structure when we have a global social network where everyone is connected to everyone. It is difficult to imagine a functional politics building on that.

Ars Technica: I want to come back to your comment on the power law distribution, how 1 percent of people dominate the conversation, because I think that is something that most users routinely forget. The horrible things we see people say on the Internet are not necessarily indicative of the vast majority of people in the world. 

Petter Törnberg: For sure. That is capturing two aspects. The first is the social media prism, where the perspective we get of politics when we see it through the lens of social media is fundamentally different from what politics actually is. It seems much more toxic, much more polarized. People seem a little bit crazier than they really are. It’s a very well-documented aspect of the rise of polarization: People have a false perception of the other side. Most people have fairly reasonable and fairly similar opinions. The actual polarization is lower than the perceived polarization. And that arguably is a result of social media, how it misrepresents politics.

And then we see this very small group of users that become very influential who often become highly visible as a result of being a little bit crazy and outrageous. Social media creates an incentive structure that is really central to reshaping not just how we see politics but also what politics is, which politicians become powerful and influential, because it is controlling the distribution of what is arguably the most valuable form of capital of our era: attention. Especially for politicians, being able to control attention is the most important thing. And since social media creates the conditions of who gets attention or not, it creates an incentive structure where certain personalities work better in a way that’s just fundamentally different from how it was in previous eras.

Ars Technica: There are those who have sworn off social media, but it seems like simply not participating isn’t really a solution, either.

Petter Törnberg: No. First, even if you only read, say, The New York Times, that newspaper is still reshaped by what works on social media, the social media logic. I had a student who did a little project this last year showing that as social media became more influential, the headlines of The New York Times became more clickbaity and adapted to the style of what worked on social media. So conventional media and our very culture is being transformed.

But more than that, as I was just saying, it’s the type of politicians, it’s the type of people who are empowered—it’s the entire culture. Those are the things that are being transformed by the power of the incentive structures of social media. It’s not like, “This is things that are happening in social media and this is the rest of the world.” It’s all entangled, and somehow social media has become the cultural engine that is shaping our politics and society in very fundamental ways. Unfortunately.

Ars Technica: I usually like to say that technological tools are fundamentally neutral and can be used for good or ill, but this time I’m not so sure. Is there any hope of finding a way to take the toxic and turn it into a net positive?

Petter Törnberg: What I would say to that is that we are at a crisis point with the rise of LLMs and AI. I have a hard time seeing the contemporary model of social media continuing to exist under the weight of LLMs and their capacity to mass-produce false information or information that optimizes these social network dynamics. We already see a lot of actors—based on this monetization of platforms like X—that are using AI to produce content that just seeks to maximize attention. So misinformation, often highly polarized information as AI models become more powerful, that content is going to take over. I have a hard time seeing the conventional social media models surviving that.

We’ve already seen the process of people retreating in part to credible brands and seeking to have gatekeepers. Young people, especially, are going into WhatsApp groups and other closed communities. Of course, there’s misinformation from social media leaking into those chats also. But these kinds of crisis points at least have the hope that we’ll see a changing situation. I wouldn’t bet that it’s a situation for the better. You wanted me to sound positive, so I tried my best. Maybe it’s actually “good riddance.”

Ars Technica: So let’s just blow up all the social media networks. It still won’t be better, but at least we’ll have different problems.

Petter Törnberg: Exactly. We’ll find a new ditch.

DOI: arXiv, 2025. 10.48550/arXiv.2508.03385  (About DOIs).

Photo of Jennifer Ouellette

Jennifer is a senior writer at Ars Technica with a particular focus on where science meets culture, covering everything from physics and related interdisciplinary topics to her favorite films and TV series. Jennifer lives in Baltimore with her spouse, physicist Sean M. Carroll, and their two cats, Ariel and Caliban.

Study: Social media probably can’t be fixed Read More »

fanfic-study-challenges-leading-cultural-evolution-theory

Fanfic study challenges leading cultural evolution theory


Fanfic community craves familiarity much more than novelty—but reports greater enjoyment from novelty.

Credit: Aurich Lawson | Marvel

It’s widely accepted conventional wisdom that when it comes to creative works—TV shows, films, music, books—consumers crave an optimal balance between novelty and familiarity. What we choose to consume and share with others, in turn, drives cultural evolution.

But what if that conventional wisdom is wrong? An analysis based on data from a massive online fan fiction (fanfic) archive contradicts this so-called “balance theory,” according to a paper published in the journal Humanities and Social Sciences Communications. The fanfic community seems to overwhelmingly prefer more of the same, consistently choosing familiarity over novelty; however, they reported greater overall enjoyment when they took a chance and read something more novel. In short: “Sameness entices, but novelty enchants.”

Strictly speaking, authors have always copied characters and plots from other works (cf. many of William Shakespeare’s plays), although the advent of copyright law complicated matters. Modern fan fiction as we currently think of it arguably emerged with the 1967 publication of the first Star Trek fanzine (Spockanalia), which included spinoff fiction based on the series. Star Trek also spawned the subgenre of slash fiction, when writers began creating stories featuring Kirk and Spock (Kirk/Spock, or K/S) in a romantic (often sexual) relationship.

The advent of the World Wide Web brought fan fiction to the masses, starting with Usenet newsgroups and mailing lists and eventually the development of massive online archives where creators could upload their work to be read and commented upon by readers. The subculture has since exploded; there’s fanfic based on everything from Sherlock Holmes to The X-Files, Buffy the Vampire Slayer, Game of Thrones, the Marvel Cinematic Universe, and Harry Potter. You name it, there’s probably fanfic about it.

There are also many subgenres within fanfic beyond slash, some of them rather weird, like a magical pregnancy (Mpreg) story in which Sherlock Holmes and Watson fall so much in love with each other that one of them becomes magically pregnant. (One suspects Sherlock would not handle morning sickness very well.) Sometimes fanfic even breaks into the cultural mainstream: E.L. James’ bestselling Fifty Shades of Grey started out as fan fiction set in the world of Stephenie Meyer’s Twilight series.

So fanfic is a genuine cultural phenomenon—hence its fascination for Simon DeDeo, a complexity scientist at Carnegie Mellon University and the Santa Fe Institute who studies cultural evolution and the emergence of social hierarchies. (I reported on DeDeo’s work analyzing the archives of London’s Old Bailey in 2014.) While opinion remains split—even among the authors of the original works—as to whether fanfic is a welcome homage to the original works that just might help drive book sales or whether it constitutes a form of copyright infringement, DeDeo enthusiastically embraces the format.

“It’s the dark matter of creativity,” DeDeo told Ars. “I love that it exists. It’s a very non-elitist form. There’s no New York Times bestseller list. It would be hard to name the most famous fan fiction writers. The world building has been done. The characters exist. The plot elements have already been put together. So the bar to entry is lower. Maybe sometime in the 19th century we get a notion of genius and the individual creator, but that’s not really what storytelling has been about for the majority of human history. In that one sense, fan fiction is closer to what we were doing around the campfire.”

spock lying down in sick bay while kirk holds his hand tenderly at his bedside

Star Trek arguably spawned contemporary fan fiction—including stories imagining Kirk and Spock as romantic partners. Credit: Paramount Pictures

That’s a boon for fanfic writers, most of whom have non-creative day jobs; fanfic provides them with a creative outlet. Every year, when DeDeo asks students in his classes whether they read and/or write fanfic, a significant percentage always raise their hands. (He once asked a woman about why she wrote slash. Her response: “Because no one was writing porn that I wanted to read.”) In fact, that’s how this current study came about. Co-author Elise Jing is one of DeDeo’s former students with a background in both science and the humanities—and she’s also a fanfic connoisseur.

Give them more of the same

Jing thought (and DeDeo concurred) that the fanfic subculture provided an excellent laboratory for studying cultural evolution. “It’s tough to get students to read a book. They write fan fiction voluntarily. This is stuff they care about writing and care about reading. Nobody gets prestige or power in the larger society from writing fan fiction,” said DeDeo. “This is not a top-down model where Hollywood is producing something and then the fans are consuming it. The fans are producing and consuming so it’s a truly self-contained culture that’s constantly evolving. It’s a pure product consumption cycle. People read it, they bookmark it, they write comments on it, and all that gives us insight into how it’s being received. If you’re a psychologist, you couldn’t pay to get this kind of data.”

Fanfic is a tightly controlled ecosystem, so it lacks many of the confounding factors that make it so difficult to study mainstream cultural works. Also, the fan fiction community is enormous, so the potential datasets are huge. For this study, the authors relied on data from the online Archive of Our Own (AO3), which boasts nearly 9 million users covering more than 70,000 different fandoms and some 15 million individual works. (Sadly, the site has since shut down access to its data over concerns of that data being used to train AI.)

According to DeDeo, the idea was to examine the question of cultural evolution on a population level, rather than on the individual level: “How do these individual things agglomerate to produce the culture? “

Strong positive correlation is found between the response variables except for the Kudos-to-hits ratio. Topic novelty is weakly positively correlated with Kudos-to-hits ratio, but negatively correlated with the other response variables.

Strong positive correlation is found between the response variables except for the Kudos-to-hits ratio. Topic novelty is weakly positively correlated with Kudos-to-hits ratio but negatively correlated with the other response variables. Credit: E. Jing et al., 2025

The results were striking. AO3 members overwhelmingly preferred familiarity in their fan fiction, i.e., more of the same. One notable exception was a short story that was both hugely popular and highly novel. Simply titled “I Am Groot,” the story featured the character from Guardians of the Galaxy. The text is just “I am Groot” repeated 40,000 times—a stroke of genius in that this is entirely consistent with the canonical MCU character, whose entire dialogue consists of those words, with meaning conveyed by shifts of tone and context. But such exceptions proved to be very rare.

“We were so stunned that balance theory wasn’t working,” said DeDeo, who credits Jing with the realization that they were dealing with two distinct pieces of the puzzle: how much is being consumed, and how much people like what they consume, i.e., enjoyment. Their analysis revealed, first, that people really don’t want an optimized mix of familiar and new; they want the same thing over and over again, even within the fanfic community. But when people do make the effort to try something new, they tend to enjoy it more than just consuming more of the same.

In short, “We are anti-balance theory,” said DeDeo. “In biology, for example, you make a small variation in the species and you get micro-evolution. In culture, a minor variation is just less likely to be consumed. So it really is a mystery how we evolve at all culturally; it’s not happening by gradual movement. We can see that there’s novelty. We can see that when people encounter novelty, they enjoy it. But we can’t quite make sense of how these two competing effects work out.”

“This is the great paradox,” said DeDeo. “Culture has to be stable. Without long-term stability, there’s no coherent body of work that can even constitute of culture if every year fan fiction totally changes. That inherent cultural conservatism is in some sense a precondition for culture to exist at all.” Yet culture does evolve, even within the fanfic community.

One possible alternative is some kind of punctuated equilibrium model for cultural evolution, in which things remain stable but undergo occasional leaps forward. “One story about how culture evolves is that eventually, the stuff that’s more enjoyable than what people keep re-consuming somehow becomes accessible to the majority of the community,” said DeDeo. “Novelty might act as a gravitational pull on the center and [over time] some new material gets incorporated into the culture.” He draws an analogy to established tech companies like IBM versus startups, most of which die out; but those few that succeed often push the culture substantially forward.

Perhaps there are two distinct groups of people: those who actively seek out new things and those who routinely click on familiar subject matter because even though their enjoyment might be less, it’s not worth overcoming their inertia to try out something new. Perhaps it is those who seek novelty that sow the seeds of eventual shifts in trends.

“Is it that we’re tired? Is it that we’re lazy? Is this a conflict within a human or within a culture?” said DeDeo. “We don’t know because we only get the raw numbers. If we could track an individual reader to see how they moved between these two spaces, that would be really interesting.”

Humanities and Social Sciences Communications, 2025. DOI: 10.1057/s41599-025-05166-3  (About DOIs).

Photo of Jennifer Ouellette

Jennifer is a senior writer at Ars Technica with a particular focus on where science meets culture, covering everything from physics and related interdisciplinary topics to her favorite films and TV series. Jennifer lives in Baltimore with her spouse, physicist Sean M. Carroll, and their two cats, Ariel and Caliban.

Fanfic study challenges leading cultural evolution theory Read More »

how-the-malleus-maleficarum-fueled-the-witch-trial-craze

How the Malleus maleficarum fueled the witch trial craze


Invention of printing press, influence of nearby cities created perfect conditions for social contagion.

Between 1400 and 1775, a significant upsurge of witch trials swept across early-modern Europe, resulting in the execution of an estimated 40,000–60,000 accused witches. Historians and social scientists have long studied this period in hopes of learning more about how large-scale social changes occur. Some have pointed to the invention of the printing press and the publication of witch-hunting manuals—most notably the highly influential Malleus maleficarum—as a major factor, making it easier for the witch-hunting hysteria to spread across the continent.

The abrupt emergence of the craze and its rapid spread, resulting in a pronounced shift in social behaviors—namely, the often brutal persecution of suspected witches—is consistent with a theory of social change dubbed “ideational diffusion,” according to a new paper published in the journal Theory and Society. There is the introduction of new ideas, reinforced by social networks, that eventually take root and lead to widespread behavioral changes in a society.

The authors had already been thinking about cultural change and the driving forces by which it occurs, including social contagion—especially large cultural shifts like the Reformation and the Counter-Reformation, for example. One co-author, Steve Pfaff, a sociologist at Chapman University, was working on a project about witch trials in Scotland and was particularly interested in the role the Malleus maleficarum might have played.

“Plenty of other people have written about witch trials, specific trials or places or histories,” co-author Kerice Doten-Snitker, a social scientist with the Santa Fe Institute, told Ars. “We’re interested in building a general theory about change and wanted to use that as a particular opportunity. We realized that the printing of the Mallleus maleficarum was something we could measure, which is useful when you want to do empirical work, not just theoretical work.”

Ch-ch-ch-changes…

The Witch, No. 1, c. 1892 lithograph by Joseph E. Baker. shows a woman in a courtroom, in the dock with arms outstretched before a judge and jury.

The Witch, No. 1, c. 1892 lithograph by Joseph E. Baker.

Credit: Public domain

The Witch, No. 1, c. 1892 lithograph by Joseph E. Baker. Credit: Public domain

Modeling how sweeping cultural change happens has been a hot research topic for decades, hitting the cultural mainstream with the publication of Malcolm Gladwell’s 2000 bestseller The Tipping Point. Researchers continue to make advances in this area. University of Pennsylvania sociologist Damon Centola, for instance, published How Behavior Spreads: the Science of Complex Contagions in 2018, in which he applied new lessons learned in epidemiology—on how viral epidemics spread—to our understanding of how social networks can broadly alter human behavior. But while epidemiological modeling might be useful for certain simple forms of social contagion—people come into contact with something and it spreads rapidly, like a viral meme or hit song—other forms of social contagion are more complicated, per Doten-Snitker.

Doten-Snitker et al.’s ideational diffusion model differs from Centola’s in some critical respects. For cases like the spread of witch trials, “It’s not just that people are coming into contact with a new idea, but that there has to be something cognitively that is happening,” said Doten-Snitker. “People have to grapple with the ideas and undergo some kind of idea adoption. We talk about this as reinterpreting the social world. They have to rethink what’s happening around them in ways that make them think that not only are these attractive new ideas, but also those new ideas prescribe different types of behavior. You have to act differently because of what you’re encountering.”

The authors chose to focus on social networks and trade routes for their analysis of the witch trials, building on prior research that prioritized broader economic and environmental factors. Cultural elites were already exchanging ideas through letters, but published books added a new dimension to those exchanges. Researchers studying 21st century social contagion can download massive amounts of online data from social networks. That kind of data is sparse from the medieval era. “We don’t have the same archives of communication,” said Doten-Snitker. “There’s this dual thing happening: the book itself, and people sharing information, arguing back and forth with each other” about new ideas.

Graph showing the stages of the ideation diffusion model

The stages of the ideation diffusion model.

Credit: K. Dooten-Snitker et al., 2024

The stages of the ideation diffusion model. Credit: K. Dooten-Snitker et al., 2024

So she and her co-authors et al. turned to trade routes to determine which cities were more central and thus more likely to be focal points of new ideas and information. “The places that are more central in these trade networks have more stuff passing through and are more likely to come into contact with new ideas from multiple directions—specifically ideas about witchcraft,” said Doten-Snitker. Then they looked at which of 553 cities in Central Europe held their first witch trials, and when, as well as those where the Malleus maleficarum and similar manuals had been published.

Social contagion

They found that each new published edition of the Malleus maleficarum corresponded with a subsequent increase in witch trials. But that wasn’t the only contributing factor; trends in neighboring cities also influenced the increase, resulting in a slow-moving ripple effect that spread across the continent. “What’s the behavior of neighboring cities?” said Doten-Snitker. “Are they having witch trials? That makes your city more likely to have a witch trial when you have the opportunity.”

In epidemiological models like Centola’s, the pattern of change is a slow start with early adoption that then picks up speed and spreads before slowing down again as a saturation point is reached, because most people have now adopted the new idea or technology. That doesn’t happen with witch trials or other complex social processes such as the spread of medieval antisemitism. “Most things don’t actually spread that widely; they don’t reach complete saturation,” said Doten-Snitker. “So we need to have theories that build that in as well.”

In the case of witch trials, the publication of the Malleus maleficarum helped shift medieval attitudes toward witchcraft, from something that wasn’t viewed as a particularly pressing problem to something evil that was menacing society. The tome also offered practical advice on what should be done about it. “So there’s changing ideas about witchcraft and this gets coupled with, well, you need to do something about it,” said Doten-Snitker. “Not only is witchcraft bad, but it’s a threat. So you have a responsibility as a community to do something about witches.”

The term “witch hunt” gets bandied about frequently in modern times, particularly on social media, and is generally understood to reference a mob mentality unleashed on a given target. But Doten-Snitker emphasizes that medieval witch trials were not “mob justice”; they were organized affairs, with official accusations to an organized local judiciary that collected and evaluated evidence, using the Malleus malficarum and similar treatises as a guide. The process, she said, is similar to how today’s governments adopt new policies.

Why conspiracy theories take hold

Graphic showing cities where witch trials did and did not take place in Central EuropeWitch trials in Central Europe, 1400–1679, as well as those that printed the Malleus Maleficarum.

Cities where witch trials did and did not take place in Central Europe, 1400–1679, as well as those with printed copies of the Malleus Maleficarum.

Credit: K. Doten-Snitker et al., 2024

Cities where witch trials did and did not take place in Central Europe, 1400–1679, as well as those with printed copies of the Malleus Maleficarum. Credit: K. Doten-Snitker et al., 2024

The authors developed their model using the witch trials as a useful framework, but there are contemporary implications, particularly with regard to the rampant spread of misinformation and conspiracy theories via social media. These can also lead to changes in real-world behavior, including violent outbreaks like the January 6, 2021, attack on the US Capitol or, more recently, threats aimed at FEMA workers in the wake of Hurricane Helene. Doten-Snitker thinks their model could help identify the emergence of certain telltale patterns, notably the combination of the spread of misinformation or conspiracy theories on social media along with practical guidelines for responding.

“People have talked about the ways that certain conspiracy theories end up making sense to people,” said Doten-Snitker. “It’s because they’re constructing new ways of thinking about their world. This is why people start with one conspiracy theory belief that is then correlated with belief in others. It’s because you’ve already started rebuilding your image of what’s happening in the world around you and that serves as a basis for how you should act.”

On the plus side, “It’s actually hard for something that feels compelling to certain people to spread throughout the whole population,” she said. “We should still be concerned about ideas that spread that could be socially harmful. We just need to figure out where it might be most likely to happen and focus our efforts in those places rather than assuming it is a global threat.”

There was a noticeable sharp decline in both the frequency and intensity of witch trial persecutions in 1679 and onward, raising the question of how such cultural shifts eventually ran their course. That aspect is not directly addressed by their model, according to Doten-Snitker, but it does provide a framework for the kinds of things that might signal a similar major shift, such as people starting to push back against extreme responses or practices.  In the case of the tail end of the witch trials craze, for instance, there was increased pressure to prioritize clear and consistent judicial practices that excluded extreme measures such as extracting confessions via torture, for example, or excluding dreams as evidence of witchcraft.

“That then supplants older ideas about what is appropriate and how you should behave in the world and you could have a de-escalation of some of the more extremist tendencies,” said Doten-Snitker. “It’s not enough to simply say those ideas or practices are wrong. You have to actually replace it with something. And that is something that is in our model. You have to get people to re-interpret what’s happening around them and what they should do in response. If you do that, then you are undermining a worldview rather than just criticizing it.”

Theory and Society, 2024. DOI: 10.1007/s11186-024-09576-1  (About DOIs).

Photo of Jennifer Ouellette

Jennifer is a senior reporter at Ars Technica with a particular focus on where science meets culture, covering everything from physics and related interdisciplinary topics to her favorite films and TV series. Jennifer lives in Baltimore with her spouse, physicist Sean M. Carroll, and their two cats, Ariel and Caliban.

How the Malleus maleficarum fueled the witch trial craze Read More »