A.I. as opposed to what?

One popular use of A.I. - specifically chatbots using LLMS - that I did not foresee is as a source of life advice. Sometimes, people refer to this in the context of therapy, as if the user is using ChatGPT or another A.I. as a substitute therapist. That implies a certain level of intimacy and privacy that probably applies to a minority of the many advice-seeking queries users offer every day. 

When thinking about the effects of anything, we often search for comparisons, and the comparisons we make are often shaped by metaphors we use - I think that's what is happening with how we think about the effects of using A.I. for advice-seeking. Instead of choosing a comparison that comes to mind the quickest or perhaps one that suits our existing biases for or against the phenomenon in question (e.g., how do the answers given by ChatGPT compare to those given by a professional therapist), we might choose our comparisons in a more deliberate way. Instead of starting with the connections our mind makes when learning of a few vivid exemplars, we might first define the field of inquiry - what is the behavior we're interested in, how many folks are engaging in it, and how can I observe a representative sample of it? 

The next step is to consider the behavior in the context of people's lives. Here, the choice of comparison is not what comes to mind for us, but our reasonable guess as to what people engaging in the behavior would have done otherwise. If they didn't have access to ChatGPT, who or what would they have gone to for advice (or would they have gone to anyone or anything for advice at all)? 

Therapists strike me as sources of very good advice on many topics. They're also better than self-help books because they can tailor their advice to you as an individual and they engage in a back-and-forth exchange. There's also some intangible humanity to your connection with a therapist that clearly helps. On the down side, it is hard to access therapy. There are only so many professionally trained therapists to go around. Efforts to make them more accessible by moving therapy online sacrifices some benefits of the therapeutic experience, namely the intangible human connection, in addition to leading to burnout from overbooked therapists. Even a society that is fully committed to serving the mental and emotional needs of its citizens runs up against the limits of therapeutic supply. 

Of course, people have turned to many other sources for life advice, including friends, family, clergy, authors, and artists. You may not approach a movie, TV show, or a novel with an advice-seeking intension, and yet its lessons may be your guide through any number of emotional or existential straits.

Then there are sources of advice that we encounter online: in spaces explicitly marked as such (and which derive their format and logic from newspaper advice columns) but also on YouTube, TikTok, and podcasts. Again, these life lessons may not be something we sought out, but they may still inform how we navigate challenging times in our lives. 

As I consider whether its a good idea for people to turn to ChatGPT for advice, I find that the most apt comparison - that is, the most plausible source of advice for most of the people asking ChatGPT for advice - is either googling it, searching YouTube or TikTok, or running across it on YouTube or TikTok via an algorithm. The quality of advice coming from these sources is, well, mixed. In many cases, the answers aren't as high quality as one would get from a professional, but its much more accessible, which is why its used more often. In some cases - googling something that is commonly googled and finding results from trusted sources - the quality is similar to that which you'd get from a professional. 

Are the types of life advice questions users ask ChatGPT more like the impersonal kind that people have, for the past 20 years, tended to google? Or are they more like the personal questions that people turned to friends, family, and - if they have access - therapists for? My sense is that a fair amount of young people have been getting that kind of advice from YouTube, TikTok, and other social media platforms for the past decade. In that sense, it is an appropriate point of comparison for that type of advice.

I'd imagine advice of this sort given by ChatGPT would be pretty homogeneous when compared to what you would find on social media platforms. The latter would vary greatly in values it reflected, the perspectives and experiences from which it drew. It leaves the existing variety of humanity intact, while ChatGPT probably flattens it. 

I guess I imagine cases in which people get bad life advice - "bad" in the sense that they result in some harm to themselves and/or others - being more numerous on social media platforms than on ChatGPT. I also imagine that the flat homogeneity of its answers won't necessarily spread to other aspects of culture more broadly, as some suspect it will. ChatGPT tends to qualify its advice and allow for some degree of variety and nuance in its answers. By merely asserting that there is some variety and nuance to certain life advice questions, ChatGPT would be contradicting the values of some of its users. This is less likely to happen on social media where answers are sorted by algorithm to confirm the existing biases of users. 

And so that would seem to be the trade-off: leave the echo chambers of social media advice intact - some of which generate harmful outcomes - or replace them with answers that guide most users away from harmful outcomes but homogenize...something. But is it really Culture that's being homogenized if people are encouraged to cope with crisis in particular ways? This is where my speculation reaches its limit and I feel the need for a more systematic examination of the life advice questions people ask ChatGPT and the answers they receive. 

What do we mean by "Influencer?"

One of the most fruitful panels I attended at this year's International Communication Association conference concerned the definition of "influencer." The term has always rubbed me the wrong way, always sounded like self-serving marketer-speak that misleads us about how influential anyone is online. As Crystal Abidin of Curtin University pointed out during the panel, the term is deployed strategically. If calling yourself an influencer makes you money and avoids the kind of regulation to which professional media producers are subject, then that's what you'll call yourself. 

What are the alternatives? "Content producer" is certainly less aggrandizing, but it also makes no claim with regard to reach, engagement, or any other metric of success. Even if only a few people watch my videos, I'm still a content producer. The same could be said of platform-specific or media-specific monikers like YouTuber, TikTokker, podcaster, streamer, or vlogger/blogger. There needed to be some term that differentiated online content producers with a certain level of success - however one wanted to define and measure success - from those without it. 

For a time, that term was "micro-celebrity," a name as diminishing (who wants to be thought of as a "micro" anything?) as "influencer" is aggrandizing. Aside from their opposite associations, differences in name matter for scholars, journalists, or interested members of the public seeking out research on this phenomenon. Search the databases for articles, chapters, and books on "influencers" and you'll be missing some of the most important work on the topic, like Alice Marwick's work on successful YouTubers - highly applicable to the successful TikTokkers we now refer to as "influencers." So, that was one takeaway: if you're interested in influencers, start with the scholarly work done on micro-celebrity. 

Number of followers = Influencer?

The European Commission defines Influencers as "content creators who often advertise or sell products on a regular basis." While this jibes with most people's conception of Influencers, it doesn't seem inclusive enough. It rules out anyone with a large audience who makes money through Patreon or pre-roll ads (which, I would think, is the platform advertising rather than the content creator, but the creator still gets a cut of the ad revenue) instead of overt paid promotion. Such a user might be highly influential - raising awareness of a cause or an approach to investing or a political candidate - but would not meet the strict legal definition set forth by the European Commission.

Most of the research on Influencers, both qualitative and quantitative, points to some metric - usually the user's number of followers - as evidence that they are, in fact, an influencer. As best I can tell, the cut-off for Influencer status is arbitrary and/or based on round numbers chosen by marketing professionals. The bare minimum seems to be 1,000 followers, qualifying for the lowest tier of influencer - the "nano-influencer."

In addition to metrics, there seems to be an aesthetic component to the accepted definition of Influencer. Accounts referred to as Influencers tend to feature individuals or, less frequently, duos or families, and they typically appear in all or most of their videos, typically directly addressing the camera/audience. A popular (and, perhaps, highly influential) account that compiled thematically related clips would not fit this aesthetic description nor would an account run by a group of comedians. And yet sometimes, such accounts are referred to as influencers. 

Are Influencers Actually Influential?

Why does it matter whom we call influencers? What are we assuming about them when we take them as a starting point to studying or reporting on some social phenomenon?

All members of the ICA panel seemed skeptical that everyone, or even most, influencers are especially influential, and skeptical of the direct relationship - often assumed by journalists, users, and even researchers - between follower count and influence. Marketers would tell you that "reach" is an important aspect of influence, but not the only aspect. To be influential, it helps to be well liked. And sure, the act of following an account implies affinity, but how many of those who follow an account see every post, "like" every post, and have their beliefs, attitudes, or behavior influenced by every post? A subset of followers actually see any given post, and of that, a smaller subset might be persuadable, depending on their mood and the proximity between their current beliefs and attitudes and those of the influencer.

Most press articles and more than a few academic articles and books about influencers don't make the distinction between reach and influence. At best, these models of influence lack nuance but are still fundamentally sound. All things being equal, a content creator with 1,000,000 followers is probably more influential than one with 10,000 followers. This kind of relative judgment of influence is a logic that underpins the entire advertising industry; an industry, it should be noted, that gave rise to the term "influencer." How effective is a given ad at persuading people to purchase a product? Surprisingly, it's still difficult to tell. 

Part of the reason it's difficult to tell is that companies creating and selling ads don't have much incentive to prove the magnitude of their efficacy. All they have to prove to companies seeking to promote their goods and services through advertising is the relative advantage in the marketplace compared to their competition. As long as they are more visible to potential consumers than the competition, they're more likely to sell more products or services than the competition. 

But for those of us who care less about selling one particular set of products or services and care more about influence in general (who to vote for, whether or not to get vaccinated, changing one's beliefs about capitalism or gender equality, etc.), the magnitude of influences matter. Simply equating exposure with influence puts us back at the hypodermic needle model of media effects - everyone who is exposed to a media message reacts to it the same way. That theory was debunked (or at least modified) over 60 years ago by the Limited Media Effects paradigm.

Some might argue that its different this time around. Influencers are more influential than standard mediated promotion because audiences/followers feel as though they have a relationship with the influencer (i.e. a parasocial relationship), and because influencers are perceived to be more authentic than celebrities. At times, they actually interact with audience members through comments or replies. We know that one's peers can have an influence many times greater than that of impersonal mass promotion campaigns, and the relationship between influencers and their followers is thought to be like those of peers. For the relatively few followers who repeatedly comment and receive replies from influencers (i.e., interact with them repeatedly), this seems plausible. For the majority (90-95% of followers, I'd guess) who don't, it seems more like the relationship between a talk show host and their audience - more personal (and thus more influential) than the relationship between a fictional character and an audience or mass advertising and an audience, but less than an actual close friend. Might influencers be more influential than impersonal TV advertising? Sure, but that's a pretty low bar. 

It seems most likely to me that influencers are highly influential under certain conditions. They're probably good at directing attention to people, places, or things that have yet to attract much attention. They can take an unknown product, social cause, political candidate, or location and make it enormously popular (or enormously hated) overnight. It strikes me as far less likely that influencers can get people to change their minds about a person, place, or thing once their audience already know about it and have formed an opinion about it. This is nothing new: that's how persuasion works - easy when people don't have an awareness or opinion of something or someone, difficult when they already do. Any marketer, campaign manager, or media effects researcher from 60 years ago could have told you that. So, a more accurate moniker for influencers might be "attention directors."

The Real Influencers

Consider this alternative: perhaps the people who "like," share, repeatedly view, or discuss content online have the greatest amount of influence in our current mediascape. This largely anonymous, highly engaged group is far smaller than the general public, and in most cases smaller than the audience, which includes casual, less engaged people. The influence of the highly engaged group over the influencer is subtle, but worth thinking about. 

It might help to take the perspective of someone who sets out to be an influencer. They have something they want to say, some "self" they want to express. They express it...and get very little attention from audiences. Disappointed, they take a quick scan of the most popular influencers overall and in their particular domain (say, gaming, sports, or political commentary). They get a sense of the things those people say or do that make them popular - aesthetic choices like editing pace and clarity of message, but also ideological choices, embodiments of personality, tone, language, sense of humor, etc. They begin to adopt some of these, reluctant to wander too far away from their original expression of self, both because it makes them uncomfortable and because they worry about being perceived as inauthentic. They get a bit of positive feedback - more likes, more comments, more attention - and so they keep doing it. 

The collective influence of the highly engaged audience over the influencer might be even subtler than that. Maybe the influencer watched thousands of videos while growing up, simply seeking what most audiences seek - entertainment. Through that process, they absorbed online norms, gradually developing an intuition about what differentiates popular content on a given topic and within a given online subculture from less popular content within that context. At some point, they decide to try their hand at creating content, but what it occurs to them to create - the range of expressive possibilities - is inevitably shaped by what they've already watched. They're not consciously trying to mimic the existing content that effectively caters to audiences' preferences and values, but are apt to cater to them nonetheless. That influencer becomes popular - they have hundreds of thousands of subscribers and millions of views. But what they say and how they say it must conform to the preferences and values of the highly engaged audience, or else it wouldn't become popular in the first place. 

Again, this is nothing new. Novelists, TV writers, and screenwriters know that in order to reach a large enough audience to make for a sustainable career in a capitalist marketplace, you need to - in some sense - cater to a highly influential subset of that audience (critics, opinion leaders, execs). It's crass to think that way - most creators want to see their work as pure acts of self-expression and creativity uninfluenced by the marketplace. And this is not to say that there isn't any original creativity on the part of the artist or content creator. In fact, all audiences demand it: if you simply serve them up something that already existed, they wouldn't bite. There has to be some element of novelty to it, some spark of originality, individuality, and authenticity...but it also needs to fit within a set of generic conventions, and those conventions are articulated through the habits of audiences or some highly engaged subset of the audiences. In the box office business model of media, one person's dollar is as good as another's. In the ad-supported model, certain demographics are more valued than others. And in the online attention economy, the highly engaged audience determines the downstream visibility of content, and is thus more valuable and more influential.

Reasons to be Skeptical

A lot of people want to believe that influencers (or, more broadly, any content on TikTok, Instagram, YouTube, or X/Twitter) are influential. The content creators themselves (obviously) want to believe that they have influence, and so do many researchers and journalists. It doesn't have to be so, but I think there is a bias among many who study and write about influencers to find evidence of significant influence, to protect their work against accusations of triviality, something that scholars of popular culture have dealt with for decades. My sense is that young researchers are drawn to study social media because they believe that it matters, that it is influential, so there's a bit of self-selection bias - they enter the arena looking for evidence of influence. Social media platforms want to highlight such evidence because it makes their companies more valuable, but also (somewhat less cynically) more important; their work matters. Governments, parents, and pretty much everyone else stand to benefit by ascribing blame for every social ill on social media and, by extension, influencers. There is little downside (at least for the blamers) to blaming greedy billionaires, narcissistic influencers, and opaque algorithms for social ills. Its certainly easier than fixing other long-entrenched causes of systemic inequities or one's own personal issues, or simply accepting that humans were never designed to optimize social harmony or happiness. 

That's not to say we shouldn't strive for greater social harmony and happiness; only that we should avoid seeking comfort in scapegoats. How do we know when influencers, social media platforms, or algorithms are merely scapegoats and not genuine threats? This is the hard work of good media research.

Types of audience fragmentation

 I'm embarking on a new large-scale project relating to audience fragmentation. Or rather, I have been embarking on it for the past year - such is the leisurely pace of the post-tenure research agenda. It started as a refutation of the echo chamber as an intuitive but overly simplistic characterization of audiences' media diets in the age of information abundance. Then I realized that someone already wrote that book. 

In researching the idea, I was surprised to find how few studies about fragmenting audiences and echo chambers even tried to capture what I felt was the right kind of data: data capturing the whole of people's media diets - not aggregate audience data, not what individual users post on a particular platform, not even the amount of time or what individuals see on a particular platform, but ALL of what they see across all platforms and media. Unless you capture that, you really have no way of knowing whether individuals have any overlap with one another in what content they consume and/or how many of them are sequestering themselves in ideologically polarized echo chambers. 

In defense of researchers, this is a hard kind of data to get. What media content people consume is often a private matter. It's just hard - for an academic researcher, a company, a government - to get people to trust them enough to get that data. Observing people might cause them to change their behavior. Still, some researchers have made in-roads - working with representative samples, trying to get precise, granular data on precisely what content people are seeing - and I think that if we start to piece together what they have gathered and supplement it with new data, we'll be able to get a better sense of what audience fragmentation actually looks like. 

I've started the process of collecting that data. In a survey, I've asked a sample of college students to post URLs of the last 10 TikTok videos they watched, the last 10 YouTube videos they watched, and the last 10 streaming or TV shows they watched. I'm anticipating that there will be more overlap in the TV data than in the YouTube of TikTok data. But I wonder what counts as meaningful when it comes to overlap or fragmentation. I return to the age-old question: so what?

Let's say you have a group of 100 people. In one scenario, 50 of them watch NFL highlight videos, 25 watch far-right propaganda videos, and 25 watch far-left propaganda videos. In another scenario, all 100 of them watch 100 different videos about knitting. The latter audience, as a whole, is more fragmented than the former audience. The former is more polarized in terms of the content it consumes - half of the sample can be said to occupy echo chambers, either on the right or left. 

It's clear to me while the polarization of media diets matters - it likely drives political violence, instability, etc. But why does fragmentation, in and of itself, matter? 

I guess one fear is that we will no longer have any common experiences, and that will make it harder to feel like we all live in the same society - not as bad as being ideologically polarized, but it's plausible to think that it might lead to a lack of empathy or understanding. But what counts as a common experience? Do we have to have consumed the same media text? Stuart Hall would tell you, in case you didn't already know, that different people watching the same TV episode can process it in different ways, leading to different outcomes. But at least there would be some common ground or experience. 

But what if we watched the same genre of television show, or watched the same type of video (e.g., videos about knitting)? If we contrast the 100 people who all watched different knitting videos to 100 people who all watched videos about 100 very different topics (e.g., knitting, fistfights, European history, coding, basketball highlights, lifestyle porn, etc.), I would think that the former group would have more to talk about - more common ground and experience - than the latter, despite the fact that there is an equal amount of overlap (which is to say, no overlap) in terms of each discrete video they watched. 

Instead of just looking at fragmentation across discrete texts, it would also be useful to look at it across genres or types. It could get tricky determining what qualifies as a meaningful genre or TikTok video. Some TikTok videos share a set of aesthetic conventions but may not convey the same set of values, or vice versa. There will be some similarities across the texts in people's media diets, even if there is no overlap in the discrete texts. The challenge now is to decide what similarities are meaningful. 

Micro-blogging, Take 2

As a social media platform, you know you've achieved success when others start cloning you. It's easy to call to mind the successful copycat platforms that, in several cases, far exceeded their predecessors:  Facebook (MySpace, Friendster), Reddit (Digg). It's a bit harder to recall the many clones that never make it (Voat, Google+, Orkut), typically because the network effects that are intrinsic to platforms' success put those with small userbases at a distinct disadvantage or because they lack the infrastructure and/or revenue to support a rapidly growing userbase. In other words, there typically aren't enough people to make the place interesting or valuable, or there are too many people to keep running/moderating the platform for free. 

But Meta/Facebook/Instagram's introduction of Threads is different in this regard, giving us a chance to see what a clone could do if it didn't have to worry about those two problems. Threads has already successfully ported 100 million users from Instagram, maintaining the network structure among interest/affinity groups and connections between established influencers and their audiences. It also has Meta's massive infrastructure at its disposal - growth won't be a problem. And so we have a rare opportunity to see if this version of a micro-blogging platform - already operating at a scale similar to the existing leader, Twitter - will be all that different than what came before. 

Mark Zuckerberg has pitched Threads as a friendlier version of Twitter. Broad generalizations about the emotional valence of any social space are inherently oversimplifying - you can find pockets of friendliness and hostility among virtually any large group of people, online or offline. Still, it's entirely possible that one space could have the tendency to be friendlier than another - that's an empirically testable claim (provided you can agree on how to measure "friendliness"). 

Before trying to determine whether Threads has or is likely to achieve this goal (or whether such a goal is desirable, or if friendliness and ideological heterogeneity are mutually exclusive), it's worth considering how it might go about achieving it. Most obviously, more content moderation might tamp down overt hostility. Less obviously, there are facets of the platform that affect linkages among users - which users' posts are visible to other users. 

By importing lists of followers and popular accounts from Instagram, Threads imported a set of cultural norms, one that evolved over the last decade and privileged attractive or attention-getting still images over words, audio, or video. Broadly speaking, there's a kind of showy-ness to Instagram, a content ranking system that rewards positivity (some would argue to toxic levels). Then there's the sociotechnical context in which Threads is being deployed - as a kind of antidote to Twitter's perceived problem with negativity, conflict, and abuse. If Twitter wasn't an especially friendly place before Elon Musk took it over, it is much less so now. This might create demand for such a place, which Threads is well positioned to serve.

Then there's that pesky algorithm - the necessarily obscure formula that controls which posts appear at the top of your feed. Despite widespread skepticism toward algorithms, its hard to imagine a popular social media platform without one, particular one that aspires not to link small groups of people together (e.g., Facebook, Discord, GroupMe, and the way some people use Snapchat) but to give everyone the chance - however remote - to command an audience. Imagine ranking YouTube or TikTok videos chronologically, or at random. Some weighted combination or popularity, engagement (e.g., number of comments or shares), and predicted affinity (amount of time you've spent on similar posts) is the best way to keep users coming back for more. 

One way to go about ranking posts is to defer to the masses - showcase whatever is broadly popular, as Twitter does with its prominently displayed list of trending topics. Another way is to tailor it to each user's preferences - the niche approach favored by TikTok. The first kind of ranking creates a "main character of the day" a target for attention and ridicule on and beyond the platform. The second kind, supposedly, creates echo chambers (though evidence is mounting that, as intuitive as this understanding of personalized ranking is, it doesn't fit what most users actually see on social media). Inheriting its structure from Instagram, Threads seems to privilege, as Kyle Chayka put it, banal celebrities and self-branding. As masspersonal media where any user can potentially reach millions of other users, Threads cannot help but encourage a kind of performativity over connecting with a small group. 

Then there's the shift from images and short video to text. The whole reason Threads is being talked about as a Twitter clone is because its primarily intended to be used for mass conversation. In their branching/nested structure (you can reply to a reply to a post, with each reply "nested" under the previous message), conversations on Threads resemble conversations on Reddit, and it will be interesting to see if future designs of Threads nudge users to engage more in the replies.

But I wonder about the brevity of text and what that does to conversations. The whole point of Twitter - what put the "micro" in "micro-blogging" - was the character limit (originally 140, upped to 280). It's well-suited to a fragmented attention universe, but I wonder if the tone of Twitter (witty, sure, but also mean) is an inevitable symptom of its mandatory brevity. Is there something about short-form writing that is bound to regress toward snark? Is that simply the nature of the medium, regardless of the combination of people and level of moderation? That's what Threads might give us a chance to observe.

When subreddits go dark

Among the many unforeseen effects of ChatGPT's release, there is a change in policy at Reddit that has caused a significant disruption among its community moderators. Reddit has served as a valuable and, to date, free source of training data for ChatGPT and other large language model (LLM) AI - billions of utterances from hundreds of millions of people about thousands of topics over a 15 year span. These LLM AIs are already worth billions of dollars, more than Reddit was ever worth during its first 15 years. It is therefore understandable that Reddit as a company wants to stop the practice of giving its back catalog of data away for free. They're not the only ones keen to point out that the training data used by LLMs, while ostensibly free to access, were created and facilitated by others who, it could be argued, were indispensable in the creation of now-popular AI programs like ChatGPT.

This isn't the only reason why Reddit would want to turn off the spigot of free access to its vast archives of posts and comments via an API. An ecosystem of third party apps has flourished under this policy, resulting in the loss of untold hours of user attention to ads on Reddit's official app, and thus lost revenue. Many users have become accustomed to accessing Reddit this way, and are understandably upset at having to migrate to the official Reddit app, widely regarded as inferior to the third party apps. 

Then there's the issue of how subreddit moderators use the API to more effectively moderate their communities. They can use the API to quickly assess a user's posting or comment history to see if a disruptive comment or post is part of a larger pattern and thus worth banning the user (this includes spambots and trolls that, unmoderated, could overwhelm a subreddit with useless or disruptive content). They use them to determine when a question asked by a user has already been answered in the past, and to highlight that answer. APIs are also relied upon by some users with disabilities, as a way of access the platform. This post from the moderators of r/AskHistorians has a good summary of other ways in which mods rely on the API. 

Reddit as a company seems interested in addressing the disability accessibility issue, carving out an exception for third party apps specifically designed for users with disabilities. Beyond that, they don't seem particularly interested in walking back their decision to charge for access to the API...yet. 

The conflict between the administrators (paid employees of the company) and moderators (unpaid volunteers who manage Reddit's tens of thousands of active communities) is a familiar one - management vs. labor. As with any such conflict, labor's ability to get what they want assumes that they can't easily be replaced by more willing labor - be it human or automated. Can the company still produce something of value to the consumer without the willing participation of current labor? 

In most cases, replacement labor produces something different than what was produced by the original labor, and in most cases, its (at least initially) regarded as inferior (labor certainly has an interest in highlighting its inferiority). But the question of fungibility of labor, from management's standpoint, in the world of social media is a tricky one. The culture and communities that live on popular social media platforms - the things that makes them valuable - are constantly shifting. As in most cultures and communities in the physical world, users frequently lament these shifts, blaming new entrants to the community or powerful authorities. If they hate the changes enough, they leave. 

So, when moderators of a popular subreddit choose to go on strike, effectively killing that subreddit, what happens to its users? 

One possibility is that they leave the platform. This is, I would think, what the mods are trying to accomplish - driving traffic off the platform, hurting Reddit's bottom line, and getting management some bad press. Another possibility is that the users of that subreddit migrate to other existing subreddits - ones with moderators that didn't strike - and find that these other subreddits are roughly as good at satisfying their need for distraction, information, community, amusement, comfort, etc., resulting in a surge of activity on those subreddits. Yet another possibility is that new subreddits arise to meet the demand created by the absence of striking subreddits. "Splinter" subreddits - subreddits that are created to cater to disgruntled "refugees" from a subreddit that has changed in some disagreeable way - have always been a part of the subreddit ecosystem. Modularity is a defining feature of Reddit, something that sets it apart from the single, amorphous conversation on Twitter and the atomized, fleeting comments on TikTok, YouTube, and Instagram. In this case, it makes it harder for labor to force management to do anything. Unless a critical degree of solidarity among moderators is reached and sustained (a tall order, given the number and diversity of subreddits), its hard to prevent within-platform user migration. 

Reddit's design - a feed or list of posts aggregated from subreddits to which users subscribe - can make it hard to even notice the absence of a striking subreddit. When I went to the site, it took me awhile to realize what was missing; I was still seeing pictures of cute animals, funny things that people said or did, captivating vistas and infuriating news. Of course, the impact is going to vary from user to user. For some users, access to a particular subreddit can be as valuable as access to a close friend, one whose absence would result in a sense of profound loss. It's hard to see how many users are like that - management has an interest in making it seem as though they are a small, vocal minority while labor has an interest in making it seem as though most users are upset by the changes - so upset that they are already in the process of leaving.

It's possible that a large number of currently-popular subreddits die as a result of this disruption, and that a large number of users leave the platform and don't come back. It's easy to point to moribund platforms like Digg or MySpace that never found a replacement community that could sustain the business. But that doesn't take into account the current business climate for these businesses, news organizations, and even video and audio streaming services that seem (with varying degrees of success) to be training consumers to pay - in subscription fees or attention to ads - for what they consume. If the era of free high-quality user-generated-content is over, there may be no substitutable platform for disgruntled users to migrate to. 

It also may underestimate how organic and unpredictable large groups of people are. We get used to versions of these platforms - used to seeing a certain type of post or comment at the top of the feed, the popularity of which reflects the collective sensibilities of a voting constituency of users. That sensibility persists even in the face of high turnover among contributors - it is generated not by a stable group of super-users but by a rotating cast who cater to the preferences of the constituency. Disruptions like the current one can change the voting constituencies and thus change what we see at the top of our feeds. Perhaps mods' lack of free access to APIs will make it effectively impossible to manage subreddits beyond a certain size (say, 1,000 active contributors), leading to a Reddit with no large communities and more moderately sized communities that, when they grow unmanageably large, spawn offshoots - something a bit more like Discord. That version of Reddit might be far more diverse in its interests and sensibilities, and ultimately more successful, than the version we're now accustomed to.

Futures of Twitter: Scenario Testing

Yes, I've railed against the appetite for future forecasting in this blog before. In fact, pretty much every post from the past few years is, in its own way, a screed against the kind of prediction of complex systems of long periods of time that news readers and journalists who interview academics can't seem to get enough of. And yet, when something "big" happens - a pandemic, the election of Donald Trump, Elon Musk taking over Twitter - I feel the same insatiable pull toward forecasting that everyone else feels. These are important events with far-reaching implications, and so despite their complexity, we can't seem to just say, "who knows what will happen!" We have to venture a guess.

And not just any guess. When we see worst-case-scenarios as plausible, we detest a future in which we ignored the threat so much that we have to predict doom. The unpleasantness of comprehending those futures is outweighed by our fear of feeling guilty about (and of being guilty of) not having done enough to prevent them. The other side of the argument is that there has never been a time in human history when worst-case-scenarios weren't plausible, and to spend time constantly ringing alarms is both joyless and unproductive, and that our inability or unwillingness to recall the false alarms of yesterday keeps us from learning anything about how complex systems actually work, to actually improve our prediction accuracy, and - by extension - to improve our world. I do get both sides of that argument, and so to me it seems unresolvable. 

So, to further refine my stance against long-term predictions about complex systems (the global economy, geopolitics, culture, developments in technology, etc.), I'll say that I prefer something less like predicting whether some event will spell doom for society (super vague, no timeline for when "doom" will occur, what shape it will take, etc., and so unfalsifiable) and more like fivethirtyeight's scenario testing. You start with several plausible scenarios - each one mutually exclusive to the degree that it's possible, and fairly specific about outcomes and timelines but not so specific as to be inevitably falsified by some minor quirk of history. This, at least, would allow us to learn something if our predictions are wrong, allow us to do a post-mortem and see what we missed, what variables we weighed too heavily, etc. Of course, this is dissatisfying if you are a doom-predictor because all the learning in the world won't amount to a hill of beans after the apocalypse that you failed to predict! But assuming there's at least a few people left on planet Earth, learning will be a good thing. To my mind, entertaining somewhat optimistic scenarios isn't mutually exclusive with being prepared for (though not actually predicting) the worst. 

In that spirit, here are a few scenarios regarding Musk's takeover of Twitter, some more optimistic than others. They use three metrics of success/failure: financial success (does the company turn a profit, stay solvent, continue to exist), cultural relevance (does the general public care about what's said on Twitter as much as they do now, more than they do now, or less than they do now? Does some other platform become the proxy for vox populi that Twitter is right now?), and "externalities" (affective polarization, political violence, political revolutions, cancelling/calling out people. Externalities could be both "good" [revolts against dictatorships, publicly shaming those who deserve it] or "bad" [downfalls of democracies, publicly shaming those who don't deserve it]).

Scenario 1: Financial success with lower cultural relevance and few "externalities." The most intriguing part of Musk's takeover to me, so far, is his apparent willingness to blow up the existing way that Twitter makes (or attempts to make) money. Perhaps the changes he instates drive user count WAY down, but this won't necessarily make Twitter less of a financial success. He could charge a portion of users $8, or pay the 100 most followed $1,000,000 and charge anyone who tweets more than 100 times a year $50 (a kind of 'lottery-ticket' model that, when you think about it, isn't that different than would-be filmmakers shelling out for expensive equipment and film school for a crack at a studio contract). My personal favorite idea is Willy Staley's "congestion pricing" plan - when a certain number of users have tweeted about a topic, the price of tweeting about it increases, which would - in theory - encourage people to tweet less about trending topics and more about a diverse array of topics. Or maybe a revived Vine drives profits and allows Twitter to continue to be a loss leader. Regardless of how he does it, it's possible that Twitter becomes profitable.

Meanwhile, the platform loses some of its cultural cache. The behavior (on Twitter and off) of Musk and a handful of high-profile Twitter users who would have been regulated under the old regime turns off journalists and tastemakers to such a degree that they stop paying attention to it (regardless of how outlandish it is) and pay more attention to how YouTubers, TikTokkers, and podcasters react to the day's events. Twitter will always have the brevity and "portability" of text on its side - it's easier, in the course of conversation, to tell someone what another person Tweeted than to try to describe even a short video. So, maybe a Twitter alternative (short text, highlighting trending topics) pops up and steals at least part of the cultural spotlight from Twitter. 

Regarding "externalities," there's no convincing evidence that what people say on Twitter causes political violence, revolutions, voter intimidation, cancelling, etc. These things happened before and they continue to happen, but it's just as easy to point to what people are saying on TikTok, YouTube, and podcasts as it is to point to what people are saying on Twitter as the cause of it, and so the argument that a Musk-led Twitter is leading to the downfall of society never really gains traction. 

Scenario 2: Financial success with the same level of cultural relevance and no apparent increase in externalities. Same as Scenario 1 except people (journalists, podcasters, YouTubers, TikTokkers, and - by extension - people who pay attention to what those people have to say) keep paying attention to Twitter. Maybe what's said on Twitter doesn't change all that much, or maybe it turns into a different kind of dumpster fire that people can't ignore. This is basically a kind of 'status quo' scenario. Sure, somethings change (the way Twitter monetizes users, the number of users, the character of the userbase), but no seismic changes to culture or to Twitter as a corporate entity. To me, this still feels like the most likely scenario. Habit and inertia are powerful forces - people will want to keep using the platform they've gotten into the habit of using, and reporters will want to keep referring to Twitter as vox populi. The bulk of everyday users who don't engage with trending topics will muddle along - perhaps as long as they have no interest in reaching large audiences with their tweets, they'll be allowed to use the platform for free. 

Scenario 3: Financial success with the same level of cultural relevance and "bad" externalities. In this scenario, there are a few instances of political violence that can be clearly and obviously linked to what people say on Twitter. Musk will point out that people are saying the exact same things on other platforms like YouTube and TikTok and that his company is being judged by a double-standard, but the sizable portion that already has it in for him won't want to hear it. On a "normal" ad-supported social media platform, this would start a death spiral - advertisers pull out, revenue craters, and they can't keep the lights on. But it's interesting to consider what would happen if Musk pivoted away from an ad-supported model, which he already seems to be doing. How bad and/or obvious would the externalities have to get before governments blocked the platform? I suppose middle-layer companies (occupying the space between users and platforms) like Apple, Alphabet, and AT&T might say 'enough is enough' and drop Twitter, but then maybe Musk uses Starlink to do an end run around them! This sounds a bit far-fetched to me, but you never know. 

Scenario 4: Financial failure. Enough high-profile Twitter users leave that the platform becomes less attractive to many everyday users, and the ad-supported models becomes unviable. Musk's attempts to charge subscription fees results in users trying to circumvent the fees, leading to draconion crack-downs, further turning off everyday users who head over to YouTube, TikTok, podcasts, Reddit, and Twitter clones. It's odd to think of a platform that still has cultural cache going belly up, but to some extent this is what happened to Vine. If you can't make the numbers work, your impact on culture is a moot point - you just cease to exist...or you get acquired, sold off, merged, etc. What might Twitter's afterlife look like if that happens? 

This, I think, gets us to focus on particular observables - financials, number of users, the extent to which people are talking about/paying attention to what's said on Twitter, political disruption - which is all I'm really hoping for in conversations about the future. 

How platform-specific is influence?

In the past, I've railed against making predictions about the future as a way to understand the present. This is different than predictions used as a way of dealing with uncertainty through humor - a pretty common, totally understandable reaction to crises. I'm thinking more of op-ed hot takes that seem to want to be taken seriously.

Predictions like this are often so vague that they're impossible to prove wrong. For example, if I predict that Twitter/Facebook/Reddit will die/fail, how and when will I know if this turns out to be true? If their userbases, sometime over the next 5 years, decline by 35%, have they died/failed? How about 50%? Do we have to wait another 5 years to judge the prophecy? There's also the problem of lacking a counterfactual. If something horrible happens after someone uses social media, we can't compare it to a world in which they did not use social media. It's possible the horrible thing would have happened anyway (or perhaps something even...horribler?), just through some other mechanism. There is no disincentive for continuing to make bold, wrong predictions because there is no mechanism for keeping score, no highly visible public record of wrong takes (though spectacularly wrong takes do tend to catch flak).

And yet I'm finding it hard not to use the occasion of Elon Musk's (apparently successful?) attempt to buy Twitter as a time to indulge in some predictions. I'll compensate for this indulgence by offering something more in the spirit of this blog - using the occasion as a way to gain insight into something more general about the uses and impact of social media. But first...

I can think of two likely scenarios:

Scenario 1: very little changes. Twitter use habits, like any kind of habit, are hard to change. There have been many instances in which social media platforms have done something that users have not liked, but most users do not then abandon the platform. We can more easily recall the instances in which they did abandon the platform: MySpace and Digg come to mind for me. But it seems that nearly every significant change to a platform - be it functionality, moderation policy, or ownership - tends not to result in a wholesale change in user behavior. The "culture" of Twitter may change, but linking this to Musk's ownership can be a tricky claim to verify, as cultures are always changing. In this scenario, there is no massive change in Twitter discourse (i.e., who participates and what is said or amplified) that can be directly and obviously linked to Musk's ownership of the platform. A handful of influential Twitter users on the Left will defect, as will a few hundred thousand less-influential users (including many journalists who will write about the experience). They will be displaced by a few newly influential users on the Right and a few hundred thousand less-influential tech bros and Far Right/Alt Right users. Musk might put the worst of the Far Right users in seemingly random "time outs," less out of any political conviction and more to reassert dominance get a laugh at their righteous indignation at having their trust betrayed. Losing the revenue they generate through ad exposure or subscriptions won't hurt, but the board will chastise him for playing fast and loose and he'll promise to be better. Pundits will pin everything the Right does on Musk and Twitter, but the connection won't be obvious and the claims won't be of interest to anyone outside of a bubble of journalists, news junkies, and academics. I consider this the more likely of the two scenarios. 

Scenario 2: things go poorly, less because of how Musk changes the functioning of the site and more because of the signal it sends to current and potential users. Far Right fringe groups and apolitical trolls will see Musk's unwillingness to regulate content as an invitation to push things as far as they can, inciting small-but-significant numbers of Far Right "activists" to engage in terrorism and assassination. A handful of violent political acts will be linked to Twitter in a way that will seem obvious and undeniable, not just to readers of New York Times opinion pieces but to the average politically-disengaged citizen, who will come to associate Musk and all his brands (e.g., Tesla, SpaceX) with toxicity rather than innovation. Musk will then belatedly recognize the damage to his brands and sell the company. 

So as to make these scenarios more falsifiable, I'll say that one will happen by the end of 2023. 

With that out of the way, I'll return to the title of the blog post, returning to a topic that I'd like to write about at greater length in the future: what is the nature of influence on social media platforms, and how does it differ (in duration, scope, domain-specificity, etc.) from mass media or face-to-face influence?

In thinking about the possibility of influential Twitter users defecting to another platform, I realized that platform-abandonment might involve losing one's audience and the attendant influence. All fine and well to say "follow me to YouTube/TikTok/Substack/Tumblr/Medium/Mastadon/whatever!", but it's hard to coordinate a mass exodus to another platform, and harder still to sustain that interest over time, especially when the new content home offers more of an a la carte content experience rather than the smorgasbord we've come to expect from popular platforms. Smaller platforms have trouble handling large influxes of digital refugees. Perhaps especially high-profile influencers will easily move their following to another platform (or to podcasting), but what of the Twitter users with followings of 500 to 50,000? How portable is their influence? 

Those who jump ship may lose some of their audience but find a more intimate relationship between themselves and a smaller group of followers on another platform, and this may be more rewarding for them. Those who stick around a less-regulated Twitter may find themselves in more direct battles with other users with whom they disagree than had previously been the case. The 'block' function and tweaks to the much-discussed-but-poorly-understood algorithms will help determine how easy it is for users to tolerate dissent in the name of maintaining influence. But no matter how it shakes out, I think we can learn something about influence by seeing what happens to the public personae of Twitter users with decent-sized followings who leave Twitter. Maybe Twitter's loss will be YouTube's/TikTok's/Substack's/Tumblr's/Reddit's gain, both in terms of users and in terms of cultural influence, however one chooses to define and measure that slippery concept.  

Experts Worry: Predictive News Headlines in the Age of COVID-19

Cataclysms, personal or shared, have a way of distorting your perception of time.

March 12th, 2020 was the day that I felt the Coronavirus crisis escalate. That day, I felt as though I was living simultaneously in three distinct realities. First and most vividly, there was the physical world around me. It was one of those blissful early spring days - bright and breezy. Some friends were meeting up at the local watering hole for a happy hour that was tinged with a different energy than previous ones. I think we knew it might be the last time we'd see each other in person for awhile, but this didn't make us glum. Instead, there was a kind of enhanced camaraderie, laughing at the craziness of it all, because what else was there to do?

Then, existing in what seemed like another universe, there was the reality that existed inside my computer and phone, on news websites and social media: a world quickly falling apart. There was an ever-escalating series of fear-evoking stories, every one of them true.

And then there was the thing itself: the unknowable reality of threat posed by the virus. Though the virus itself is knowable insofar as we are able to know viruses and what they do to various types of human bodies, the matter of immediate concern - the precise way the virus will spread through a given population and affect each individual person - could not be known. That reality is contingent upon too many things to be knowable, at least in mid-March, and perhaps now in early May and for the foreseeable future. The threat of the virus depends on future government policies at federal, state, and local levels, future workplace policies, the speed with which treatments will be developed and manufactured, and the future behavior of billions of individuals, as each individual's decision to, say, stay home and watch Netflix or say 'fuck it' and go out to a bar (when bars were/will be open) affects all downstream outcomes. Scientists of various stripes can imperfectly predict the spread of the virus and its deadliness by looking at various models based on prior behavior, but they cannot as yet know with absolute certainty (or really much certainty at all, it would seem) who the virus will infect in a particular social context, when it will infect them, how long it will stick around a population, who or how many it will kill.

As I moved into the gently mandated quarantine stage of the event, I started to think more about the disjuncture among these three worlds. A couple of months previous, I'd had time to think about the ways in which the social internet (news, commentary about current events on social media) presented its users with a distorted view of the world. The long and short of it is this: it enhances threats.

In the case of the virus, the threats are multiple. There is the virus itself, and then there is the effect of virus containment on the economy. Also, as always in the U.S. and perhaps elsewhere, there is the threat of the other political tribe: Would Trump invoke martial law? Would protesters spread the virus? Would liberals exaggerate the threat to make Trump look bad?

The key word in all of these questions is 'would.' I came to realize that many of the headlines I read contained words like 'would,' 'could,' 'may.' Some of the bolder ones contained the word 'will.'

They were about bad things that had not happened yet. 

On a podcast from mid-March, Malcolm Gladwell recounted something he had read that day that quoted experts from the University of California San Francisco, a leading medical school. The experts predicted that there would be more than 1 million Americans deaths from the virus.

From March 17, 2020 on the New York Times: 'There may be two to four more rounds of social distancing.'

And later, from CNN.com on April 14th, 2020: 'US may have to keep social distancing until 2022, scientists predict.'

From May 4th in the Washington Post: 'Draft report predicts covid-19 cases will reach 200,000 a day by June 1.' This article alluded to a leaked report from the CDC that also predicted that there will be 3,000 deaths per day in the second half of May.

These headlines were accompanied by opinion-piece headlines that would have seemed more at home on less prestigious news websites a few months ago. From the New York Times: 'One simple idea explains why the economy is in great danger'; 'Stop saying everything is under control. It isn't'.' 'More severe than the great recession.'

Most of the headlines and stories quoted experts who offered informed predictions about the virus or the economy. Right away, I thought of Phil Tetlock's work on expert political judgment. Tetlock found that when political experts of all ideological stripes were forced to make falsifiable predictions about a range of outcomes, they were not much better than chance or non-experts. The more famous the experts were, the worse their prediction records were. In his book The Signal and the Noise, Nate Silver reviews the incentives experts have to make predictions, why they are rewarded for more outrageous predictions with more coverage and fame, and why they are not punished for being wrong.

There are various lessons you might take away from Tetlock's ongoing project to assess the ability of experts to forecast a range of outcomes. The one I keep coming back to is that forecasting any outcomes that involve a large number of people's behavior is really difficult. The more people that may influence the outcome (that is, the more people who's individual behavior is part of the system you're trying to observe and extrapolate from), the harder the outcome is to predict.

Some of the predictions about the virus and the economy that dominated headlines were not falsifiable, as they did not provide a time range and thus could eventually be proven true even if they were not true on a particular date (they would never be false, but simply not true yet). But many were falsifiable: they made specific predictions about the duration or magnitude of an economic recession or depression; they made specific predictions about the number of infections or deaths resulting from the virus (the falsifiability of which assumes you accept data collected by authorities).

Sometimes, the experts would try to convey their levels of uncertainty in their predictions. Sometimes, they would not. Most times, this uncertainty level would not be conveyed in the news article; it was almost never conveyed in the headlines.

Aside from the inherent unpredictability of large groups of people, there is another reason why many forecasts relating to the virus or the economy will turn out to be wrong. Predictions like this can function as warnings that are then heeded by people who take action, which prevents the predicted outcome from occurring. Nate Silver calls this a 'self-cancelling prediction' or 'self-cancelling prophecy.' Similar problems plague predictions about environmental catastrophe: the more dire the predictions, the more likely they are to spur innovation or regulation that prevents the predictions from coming true.

I wonder if some folks are engaging in a kind of deliberately misleading, exaggerating framing of virus threats. Perhaps journalists and those who post on social media are aware of the shortcomings of the data they are working with, aware that they are focusing on the most dire scenarios and ignoring others. They do this because they believe, rightly, that the more dire the predictions, the more likely they will be to spur action that will prevent the more dire predictions from coming true.

I think that people often derive the wrong lesson from self-cancelling predictions. They do not prove the predictions to have been correct. It is possible that the prediction would have been wrong had no action been taken. In and of themselves, they do not provide much evidence of the accuracy of the prediction. I think the better lesson to draw from the possibility of self-cancelling predictions is that in order to have faith in our predictions in which those who learn of the prediction might plausibly affect its outcome, we must understand the mechanisms by which the predicted outcome will or won't occur. We must be able to account for the effects of particular behaviors in isolation (e.g., the effect of social distancing on viral transmission; the effect of carbon monoxide on sea levels) in order to really understand and predict complex phenomena.

The recent spate of predictive headlines brings to mind another domain examined in Nate Silver's book: weather predictions. Meteorologists' predictions of the weather on any given day were often wrong; no surprise there, as weather is another complex, hard-to-predict system. What's interesting is that the errors were systematic: meteorologists tended to predict rain on days that turned out to be sunny more often than they predicted sun on days that turned out to be rainy. As a reason for this, Silver noted that meteorologists were 'punished' for one type of wrong answer more severely than they were for the other. Most people saw sun on a supposedly rainy day as a pleasant surprise, while they tended to get angry at meteorologists who failed to warn them about the negative outcome: rain on a supposedly sunny day.

Many of the predictions dominating news headlines will inevitably turn out to be wrong, but will they be systematically wrong, wrong in a particular direction? I suspect that most journalists and news consumers see virus infections, deaths, and economic hardship in much the same way people see rain: they would rather the predictions turn out to have been too dire than not dire enough.

However, this creates a problem. If the predictions about virus infections and deaths are unnecessarily dire, this will cause consumers to spend less and investors to invest less, leading to worse economic outcomes. If the predictions about the economy are too dire, policy makers, business owners, voters, and consumers will push for re-opening too soon, resulting in worse health outcomes. All unnecessarily dire predictions will likely harm people's mental and emotional health, and any wrong prediction will harm subsequent trust in news sources.

I suspect that predictions in most mainstream news outlets will overestimate negative outcomes associated with the virus and underestimate negative outcomes associated with the economy. Of course, there's a political element to the predictions (those on the Left tend to be more concerned with the virus while those on the Right tend to be more concerned with the economy), but beyond that, I think the negative outcomes associated with the virus (mass death; dying alone) are more vivid, more viscerally repellent than those associated with the economy (lagged rises in social unrest, substance abuse, domestic abuse, and violent crime that typically accompany prolonged mass unemployment) which tend to be more diffuse and less easily depicted.

What to do about all this? Well, before going any further, it seems worthwhile to test all of my assumptions. In the spirit of putting my money where my mouth is, here are a few falsifiable hypotheses:

• The number of 'predictive headlines' (i.e., headlines that relay information about an event or state of the world that has yet to occur at the time of publication) has increased since the middle of March 2020. 

• Of the predictive headlines that are falsifiable at present, more headlines will have overestimated threats than will have correctly estimated or underestimated threats. 

• The more vivid the threat, the greater the magnitude of the error in prediction. 

• News consumers exposed to more dire predictions will be more likely to take action (or intend to take action) than those exposed to less dire predictions. 

• The inclusion of information about the confidence levels of experts (e.g., swapping out the word 'will' for the word 'could' or 'might') will have no effect on news consumers' behaviors or intentions. 

To motivate journalists and those who post on social media not to post speculative 'news,' perhaps we could shame the behavior with a catchy, albeit misleadingly reductive moniker: 'eventually fake news,' or something like that.

I can understand the desire to compulsively speculate at a time like this. Typically, there's a certain amount of uncertainty in the world. You might not know some of the details about what will happen over the next year, but you often have a rough idea of what it will be like, what you'll do, where you'll be. At a time when so much is uncertain, maybe we can't help ourselves from making predictions, even if we know most of them will turn out to be wrong. But even in times of great uncertainty, there must be something we can learn from our wrongness. Right?

‘The Curdling of the Internet’: The Open Public Sphere Internet as Threat Amplifier

A weekend retreat to a cabin in the woods provided me with time to finally get around to reading Jia Tolentino’s essay, ‘The I in the Internet.’ In a way, I’ve been thinking about what Tolentino describes as the ‘curdling’ of the internet for the past two years, since our research team started reviewing research on various forms of online hostility. More broadly, I’ve been thinking about the effects of social media on societies for the past decade.

I’m generally opposed to sweeping pronouncements about the negative effects of the internet, smartphones, or social media, mostly because it doesn’t seem to fit the evidence. Social media use, by itself, doesn’t seem to have much of an effect on well-being or depression; that is, if one person spends three hours a day on social media and the other spends one hour, or no hours, the person who uses more social media is no more likely to feel bad about themselves or about life in general. There’s also evidence that the internet exposes users to a wider range of opinions, rather than sorting users into filter bubbles or extreme echo chambers. Bad things may be happening in today’s world, and social media use might have increased at the same time, but that doesn’t mean that one caused the other to occur.

And yet, despite the apparent lack of evidence of a strong, negative effect of social media use on individuals, I can’t help but wonder if we, as researchers, are missing something, and how we might adjust so as to capture those things.

One way Tolentino’s feeling and the lack of individual, direct effects on social media users can both be true is if the internet/smartphones/social media are having a profoundly negative effect on society in general, but it occurs in some kind of indirect way. The most concise way of describing my hunch about this would be the ‘threat amplification’ effect. These technologies amplify certain voices, making certain kinds of people and behavior that were formerly invisible more visible. A sub-set of highly active social media users see the platforms as battlefields on which an ideological war is being fought, and so they post information that furthers their agendas, and/or a subset of especially passionate people simply express how strongly they feel about some issue. These expressions are perceived as threatening by a sub-set of other users, not necessarily because they contain explicit threats of violence, but maybe because they clash with some fundamental belief of theirs, or portend an escalation in the encroachment on their rights (e.g., the right to free speech; the right to exist; the right to defend themselves). These posts stick out to many people, draw attention to themselves in the way that any perceived threat in our environment sticks out to us. If future visibility of posts is determined through the amount of attention paid to them (via algorithms or 'most read' lists, etc.), then we tend to see more and more of these types of posts as time goes on.

Also, well-meaning users (journalists, re-tweeters, etc.) draw further attention to these posts in an effort to make sure that others see the threat because to ignore the threat would be hazardous. They might do so out of a sense of duty and compassion to others (i.e., they see others are in danger from the threat and must warn them) but might also do so out of self-interest, or in-group-interest. By drawing otherwise apathetic individuals’ attention to the threat, they may enlist them to join their fight. In such a way, much of the online discourse comes to resemble either a threat or a response to a threat.  

If we react to this by leaving the internet, by not participating, this may preserve our piece of mind, but it cedes the public forum of the internet to those holding more extreme views. So, perhaps we try to meet the threat with an equal and opposite assertion of our beliefs or values (which may, of course, be viewed by others as extreme and threatening). Or perhaps we just conform to the now-established norm of value-assertion-through-strong-takes in order to be heard (because in order to gain greater visibility in the form of likes, shares, and subscribers, it helps to conform to norms of what is popular), or simply because humans are prone to unconsciously conform to social norms of expression. All of these would lead to an internet that actually is becoming more threatening (again, defining 'threats' not in terms of what was intended, but how they are perceived by someone), and exposure to it would likely lead to increased polarization, depression, abuse, harassment, toxicity, etc. The internet may not have started out that way, but it could be the case that it is becoming that.

And that’s the tricky part. The internet that Robert Kraut analyzed 20 years ago in his landmark study of the effects of internet use had certain kinds of content and certain kinds of experiences and perspectives posted by users, and the internet that the research summed up in Hancock et al. has other content/experiences/perspectives, and today’s/tomorrows internet has/will have other content/experiences/perspectives. And if those three stages of the internet are sufficiently different from one another in terms of their contents, they may have very different effects. Thus, though we haven’t observed strong negative consequences of social media use, it’s impossible to rule out them occurring in the future, or right now, given the publishing lag and, perhaps, that we're looking at the wrong outcome variables.

The negative effects of internet use may not be depression, narcissism, or physical aggression. They may manifest themselves in voting behavior (e.g., voting for increasingly partisan, extreme candidates, so as to counter the perceived threat from the other side), or some other behavior that reflects a distrust in others (e.g., unwillingness to live in certain places or send one’s kids to schools with certain types of people, a kind of self-segregation). Eventually, this kind of mutual distrust may manifest itself in physical violence. Or perhaps we’ll view one another as very, very different and threatening, but ultimately leave one another alone, co-existing peacefully if not without mutual resentment (stranger things have happened).

But here’s an important limitation: everything I’ve called ‘the internet’ up until this point really refers to part of the internet: the open ‘public sphere’ internet: Twitter, Reddit, comments sections on news websites, the part of YouTube in which YouTubers engage in a kind of running commentary about the world; maybe certain users on Facebook and Instagram who use those platforms in this way. Tolentino does note that she's mostly talking about the 'social internet.' This is the part of the internet in which a single individual can post something that reaches many other individuals (one-to-many). But many of Tolentino's observations also seem to apply to news online, which is tightly linked to Twitter (the bubble that journalists live in is the bubble of the open public sphere internet). It’s worth remembering that the internet is a lot more than just this. It is Netflix and other streaming services: ‘top-down’ platforms in which content is created by a small group of professionals and consumed by a large audience. It is small-group communication via messaging apps (one-to-one, or several-to-several). Tolentino’s observations about online hostility probably don’t fit as well to small group communication online (which is 'social' and is online, though maybe it's pedantic to call it part of the 'social internet), and they only apply to Netflix and other mass media insofar as they try to reflect the zeitgeist of the open public sphere internet.   

The Open Public Sphere Internet as Difference Revealer

Now that there are so many people participating in public discourse online, the open public sphere internet has exposed groups to one another that are so unlike one another to begin with, in terms of their values, experiences, and perspectives, that independent of how aggressive or antagonistic they are, this difference is so shocking and threatening that people get freaked out. That is, it isn’t necessary to have people act in a hostile way toward another group, or in a strategic way so as to counter the messaging of others. Merely by expressing themselves, by showing who they are and what they believe, they may set others off.

Human difference was depicted and conceived in a certain way by mass media. It was often visual, concise, and fictional. So yes, traditional/legacy media depicted difference, but in a circumscribed way, made generic through the use of tropes and bracketed as fiction. While we weren’t consuming images of difference via mass media, we spent our time around people who are not terribly different in terms of beliefs, values, and experiences. We spent a lot of time around family, friends, schoolmates, and workmates. If we were out of sync in our beliefs or values, we often avoided those subjects in order to avoid conflict.

The differences that we see online are differences in values being expressed. Those differences always existed (there were always people who believed something that you would have found abhorrent), but we didn’t have to see them every day. We probably were never going to be particularly good at reacting to these differences. Many of us probably always would have perceived them as a threat to our own values. So, it could be argued that the internet is the first technology, the first moment in history, where we really have been confronted with values differences as they have always been. Of course, these online expressions are not pure reflections of any group's beliefs, are manipulated in various ways (though when we’re quickly scanning a feed and clicking on links, we may not recognize this). Nevertheless, despite the fact that they are not representative of the larger group, they are expressions of the beliefs and values of many real people. And maybe we feel this when we go online; we feel how real they are. They are not fictional characters dreamed up by a screenwriter. These are actual people who actually believe the exact opposite of what we believe.

It’s not surprising that people feel threatened by those differences. And so many folks react to the threat with a kind of siege mentality, and then many subsequent cultural expressions and public life become a reflection of that. And the only alternatives seem to be to carve out small clusters within online life via group messaging apps or forsake social media entirely.

What impact does the curdling of the open public sphere internet have on the world?

Why does any of this matter? Is it just a bunch of people bickering in cyberspace or does it have some clear connection to the rest of civic life? If some of us decide ‘to hell with it’ and only use social media for small-group communication and leave Twitter to the trolls, what would it matter?

I do wonder if the relationship between what is said on the open public sphere internet and power (political power, economic power) could change, or is changing. Perhaps when the open public sphere first became widely used in the United States, most people, including journalists and politicians, saw it as a kind of proxy for public opinion, overlooking the fact that only certain types of people expressed themselves. The apparent connection between what went on in the run-up to the 2016 election (expressions of extreme partisanship, particularly an insurgent group of Trump supporters engaging in a kind of online battle on behalf of their chosen candidate) and the outcome of that election (the election of that candidate) supports this view. 

But what if, in the coming months, the same open public sphere internet were to heap praise on Bernie Sanders and Elizabeth Warren while continuing to deride Donald Trump and deriding or ignoring Joe Biden, and Biden or Trump end up winning the election? What if that inconsistency between opinion on the open public sphere internet and a democratic election outcome were to happen a few more times in high-profile elections in different democracies? Many people might come to believe that opinion on, say, Twitter, neither reflects nor causes shifts in larger public opinion. Once this is acknowledged, I do wonder if at least some people, either in the general public or in positions of power (e.g., widely-read journalists), would be less likely to take their cues from opinion expressed on the open public sphere internet.

There’s a bit of a self-fulfilling prophecy aspect to it, I think. When people believe that Twitter is a bellweather, they look to Twitter and are subsequently influenced by opinion on Twitter. The evidence on which they initially base their belief that it is a bellweather might be suspect, but that doesn’t matter: once they believe it, they essentially bring it into being by assuming that it is public opinion writ large, are influenced by it as such, and, through their writing, influence others. That is, opinion leaders see a popular trend on Twitter and write about it as though it were popular more broadly. Others take cues from the opinion leaders and act on that information, turning it into a truly popular opinion. However, if opinion leaders stopped believing this (and again, it wouldn’t matter whether the reason they stopped believing it made much sense or was supported by evidence), they might ignore it and thus Twitter and the like would lose its power to influence public opinion writ large.

Maybe people in a certain social stratum are already leaning this way, avoiding social media (or at least the open public sphere internet) themselves, raising their kids to avoid it as well. These people are often quite powerful: upper class, working in tech, politically active. If they start ignoring opinion as expressed on the open public sphere internet, I can imagine all of it becoming like certain comment sections of certain news websites: it exists, it is ugly, but most readers simply ignore it, and it doesn’t really have much of an impact outside of itself.

In any case, it’s important to not simply assume that the open public sphere internet has a stable relationship with public opinion in general. I think it’s also worth thinking about the popularization of the open public sphere internet as the first moment in human history that we saw how different our views of the world really are, how directly they conflict with one another (there is also much agreement, though the current iteration of the open public sphere internet doesn’t seem suited to highlight that). It’s hard to imagine such a moment going smoothly. But perhaps it’s a matter of getting over the initial collective shock of it. Or perhaps we just need a little time to ourselves.

What's Wrong with News?

Since Jimmy Wales came to speak at the University of Alabama last weekend, I've been thinking more about WikiTribune, his new-ish news curation/creation venture. This seems like a rare opportunity to contribute to the building of a tool that has the backing of the creator of one of the most popular, influential, important websites in the world. Of course the venture might fail, because most new ventures fail and because news is a tricky thing to get right, maybe trickier in a lot of ways than building something akin to a library or encyclopedia. WikiTribune seems to be functioning right now as a collectively curated news aggregation website; it might evolve into something else in the future, but I'll assume that's what it is for now.

What might be the starting points for a platform like this? If news is broken (which seems a fairly uncontroversial take in 2019), what part of it could be fixed by a Wiki-type platform?

First, there's the issue of factual accuracy. A decent way of getting a newsfeed that only has news that is factually correct is just by linking to stories that are from sources that can be held accountable, that have a reputation, and that typically follow standard journalistic practices. You weed out the parody stories, the polarizing disinformation, the deliberate attempts to poison discourse with fake news. This seems like something a dedicated group of volunteers could do.

I feel like the factual accuracy problem isn't as widespread as some believe, that networks of upvoting and sharing bots only make it seem as though a handful of untrue stories are being very widely read and believed. Of course, there are most likely relatively small pockets of people who are actually believing in false stories and act on those beliefs, and despite their relatively small numbers, they can be very harmful to society. And various characteristics of popular social media platforms such as Twitter, YouTube, and Facebook (such as algorithms that don't vet information, the ability for anyone to post and share anything, being too big and too fast to moderate) increase the footprint and influence of false stories beyond what they were in the pre-internet says.

I doubt WikiTribune would lure the type of folks who seek out false stories away from their favorite hyperpartisan sites, but who knows what might happen if it eventually became even a tenth as popular as Wikipedia. Maybe it would end up as a kind of standard system for current events information vetting, a better middle layer between journalism and audiences than social media currently is. Most people would then recognize the false news stories and sources in a way that most people did before the internet: as a kind of inevitable fringe to the information ecosphere, relegated to a recognizable outskirt rather than popping up in the midst of a feed of journalism vetted in the traditional way (as tends to happen w/ news via social media). It's important to know whether factually inaccurate news exists, how much of it exists, and who is sharing and reading it, but it's also important to think about where, in our information environment, it resides. Is it concentrated or distributed? In the center or on the periphery?

During his talk, Wales brought up the problem of clickbait headlines: headlines that mislead audiences, play on our emotional, tribal, impulsive tendencies, exploit a kind of shallow curiosity. So, maybe WikiTribune curators use a kind of rough guiding principle: avoid posting clickbait headlines (or maybe just rewrite the headlines. Often, the stories are fine, but the headlines seem like they were written by search engine optimizers). Obviously, clickbait is a term with a fuzzy definition, but that's nothing new, and certainly doesn't stop websites, publishers, etc. from moderating various kinds of vaguely-defined content standard. Get multiple experienced coders to rate each headline's clickbait-iness, and when they agree, don't post it or re-write the headline.

Wales also brought up ads and their effects on content, one of which is to essentially incentivize the creation of clickbait headlines. But I guess I'm a bit unclear on how to account for the fact that many of the sources to which WikiTribune links are ad supported. Related to this, how does WikiTribune work with paywall news sites? Wales seemed to be pro-paywall, to endorse the idea that if more news sites were subscription-funded rather than ad-funded, the quality of information would improve. Would WikiTribune just give you a taste of the article, a kind of abstract or summary, something a bit more than a headline, some kind of compromise that would give the reader some value while not totally substituting for the story itself, perhaps pushing users to the full article in the way that Wikipedia might push users to the source material? That seems reasonable to me.

He also brought up algorithms. Perhaps algorithms also, in some way, guide news consumers and creators toward more clickbait-y headlines. If you have humans in the loop, maybe it would be easier to slow or stop the prevalence of clickbait and false news.

He also brought up the fact that Wikipedia is not totally open and it's not a democracy, and I think that's a way of setting this apart from the primary news aggregator of our time, Reddit. Reddit is ostensibly open, and is a kind of democracy: registered users submit and vote on content, thereby increasing or decreasing its visibility. Over time, this has led to certain kinds of news stories ending up on the front page. You might call it a product of 'hivemind.' It has a certain narrow tonal range, and a certain focus on particular topics that reflects the interests and values of the voting public.

There is recent talk of moderators playing a bigger role in directing what gets posted in subreddits, and the inevitable push-back by those who value unfettered speech and a democratic public sphere above all else. I doubt that push-back will fully subside on Reddit because voting for the noteworthiness of content is a defining characteristic of the platform. It's not ancillary in the way that 'likes' are to Instagram. But if you start a new site that simply doesn't have that as one of it's defining characteristics, you don't necessarily have that problem. Sure, a lot of people believe strongly in a flat hierarchy, an open democratic sphere, but I think that enough people have been repulsed by what that yielded to want something else.

Somewhat more controversially, we might consider the question of tone and emotion in news, and whether or not that needs 'fixing,' or could be fixed. Personally, I'm turned off by the abundance of outrage and fear that many news stories in 2019 evoke, but I recognize that an argument can be (and has been) made for the value of anger and fear in this sphere. Here, I think it's more a matter of personal preference, and not everyone would agree on this, but some would like, sometimes, to see a newsfeed that features less fear and anger. I feel like that's where a lot of popular democratic news feeds, like r/news on Reddit, end up: a kind of distilled outrage and fear.

Here, we need think about the purpose of news. Is it a kind of 'immune system' for societies that's sole purpose is to detect threats and alert us to them? Well then, it seems entirely appropriate that news would invoke anger and fear. Should news be more broad, emotionally, than that? Should it invoke wonder, curiosity, gratitude? You have subreddits like r/upliftingnews that cater to another point on the emotional spectrum, so it's not as if there isn't already a place for that in many people's information diets.

Then there's the matter of filter bubbles/echo chambers, and I don't know that there's much that WikiTribune could do about that. I think worries about filter bubbles and echo chambers are somewhat overstated and/or that we'll never fully solve that problem, and while we wait around for the perfect solution, we're making do with a pretty lousy news ecosystem that's run, by default, by impulsive clicks and a lack of accountability. I think pure democracy was one potential solution - giving the power of vetting and curation to anyone and everyone - but we've seen how well that went.

Wikipedia never solved the filter bubble problem when it came to creating an encyclopedia. The editors don't remotely reflect the readership, in terms of race, gender, education level, ideology, etc. Wikipedia isn't flawless, but it seems to be working well enough, and I gather that there is a sense within the organization that they should try to broaden the diversity of people who edit it to include more women and people of color. Should it also try to include more people who identify as politically conservative? Does it make sense to pursue intellectual diversity among information curators as well?

It looks like the current version of WikiTribune features a way to follow particular feeds curator by particular Wiki-editors. If that's the case, then what's to stop a couple of ultra-liberal or ultra-conservative editors from setting up feeds full of clickbait and partisan vitriol? Is there some overseer that decides when editors have gone too far, similar to the way that admins on Reddit ultimately have control over volunteer moderators? Might that decision as to what goes too far be motivated by one's ideology?

Yes. But I get the sense that Wikipedia has already dealt with similarly motivated people who have tried to turn Wikipedia into a more partisan information environment, and it has some sort of mechanism for dealing with them that seems to be largely effective. Is the mechanism entirely democratic and open? Probably not, but now might be the time that some of the public revisits the relationship between direct democracy and news curation and distribution.

Even if something similar to WikiTribune existed in the past (and I get the sense that that's the case) and ultimately failed, that does not determine whether WikiTribune will fail. There are many, many cases in which a creation didn't succeed because it was timed poorly. Maybe we had to wait to see how poorly open, democratic, free-for-all, algorithmic, impulsive curation of news would go before there would enough demand for something like WikiTribune to be sustainable. I'm just happy to see someone trying something like this right now.