Twitter launched their version of Stories last week (called Fleets) – some initial thoughts:
I think the Stories format fits Twitter better than any other social network because it’s actually quite similar to how Tweets work. Both Stories and Tweets are modularized content. They work as stand-alone micro content (Tweet / Fleet) or can be grouped into a bigger piece of content (Tweet storm / Story) with sub-discussions for each element.
The difference between the two formats is that Tweet discussions are public whereas Fleets will drive more usage of private discussions via Twitter DMs. This is a good thing. Twitter DMs are the most underrated part of the site (and probably the best shot any company has at disrupting LinkedIn). I just wish Twitter had improved DMs before driving more users to it.
When Instagram launched Stories, it saw that users posted less to the newsfeed – which they reserved for their best / most important photos. I wonder if we’ll see a similar trend on Twitter, but I doubt it. Tweeting photos and videos was never a great user experience, mainly because of the weird way Twitter auto-crops them, so I don’t think we’ll see cannibalization between the two formats.
The animation when swiping between Fleets feels clunky. Instagram Stories feel 10x smoother.
The creator tools for Fleets are by far the biggest disappointment. Twitter had a real chance to build something new here (personally, I think audio would be a *really* interesting format). Instead, it’s just a very limited version of other Stories features.
The Stories bar is great UI real estate for other features: I really hope Periscope will make a comeback. The rumored audio rooms would also fit nicely here.
In his bestselling book Sapiens, Yuval Harari argues that humans became the dominating species of planet earth because we are the only animal that can cooperate in large numbers. This, he claims, is due to humans’ ability to believe in purely imaginative things and concepts. A company like Google, for example, doesn’t really exist. Sure, there’s the Google.com website and physical Google offices with real Google employees – but the idea of Google as a company is just a fictional concept. It only exists because multiple people believe in it. The same is true for legal systems, nations, religion or money. Every large human cooperation system is based on a fictional idea that only lives in our collective minds.
What Harari doesn’t discuss in his book is the extreme other end of this cognitive ability: Conspiracy theories. I’ve been fascinated by Jon Glover’s recent essay on QAnon, in which he compares conspiracy theorizing to alternate-reality games. Participating in QAnon conspiracies, he says, feels like playing a real-life multiplayer game based on secret insider knowledge.
Social media has made conspiracy theorizing so addictive and immersive that the line between story and reality can become incredibly blurry.
“A lot of these groups are like cults […] They have beliefs that border on religiosity … And when you contradict them, it’s like telling them Jesus isn’t real.”
The religion analogy is interesting because it’s a perfect example of why fact checking as a countermeasure is useless. Google, Facebook & co have all introduced fact checks and fake news labels to combat conspiracy theories. It’s naive to think that they will work.
Think about it: Science (which, you could argue, is also a form of fact checking) has been around for centuries trying to debunk most religious beliefs – and yet religion still plays a major role in Western society. If entire education systems teaching millions of people about science haven’t worked, why do you think adding a small fact check disclaimer below a YouTube video would?
It’s worth pointing out that science is also just another belief system. We laugh about flat earthers, but how many people can actually explain why the world is round in a scientifically correct way? Most of us don’t know science, we believe in science.
What should give us hope though is the fact that many people believe in *both* science and religion despite their contradictions. This means that multiple realities can co-exist even when they are at odds with each other.
We don’t live in just one reality – we switch between different realities (and play different characters within them). It’s a bit like Westworld, where guests can explore different theme parks: Westworld, Shogunworld, Warworld, etc.
Similar to Westworld, it’s increasingly becoming more difficult to distinguish between what’s real and what isn’t. As Aaron Z. Lewis points out in his brilliant essay You Can Handle the Post-Truth, we have created a fragmented reality with hyper-realistic CGI influencers, bots, deepfakes, AI pretending to be humans and humans pretending to be AI. We don’t live in a single timeline with a single history, but in a variety of “contradictory reality bubbles“.
Bruno Maçães paints a similar picture in his excellent book History Has Begun. America, he believes, is in the process of transforming into a new, post-liberal society, distinct from current Western civilization. It’s a society that has not only been heavily shaped by television but one where reality and fantasy overlap.
This transformation has been in the making for a while: Kennedy had the aura of a movie star and leveraged his image through the medium of television. Nixon created the first political soap opera with the Watergate scandal. And with Reagan an actual movie star moved into the White House.
Trump is the ultimate culmination of this trend. His entire presidency feels scripted. His tweets end with cliffhangers. A House of Cards screenwriter would not have been able to come up with a better story.
Reagan and Arnold Schwarzenegger used the social capital and entertainment skills they acquired as actors to appear more likable and competent as politicians, but at least they tried to be politicians. Trump, on the other hand, uses politics as another stage for his acting performance.
“Americans see the world as an action movie” Maçães writes. I think this became especially apparent during the current covid-19 crisis and the most recent wildfires in California. People in my social media timelines seemed only superficially worried. Instead, their posts contained an underlying sense of excitement about real life finally catching up with the science fiction aesthetics of Blade Runner and Akira.
Perhaps this is Hollywood’s greatest achievement: It gets us excited about our dystopian future. The world might be ending, but at least it’s an ending that’s entertaining to watch.
If Hollywood created the fantasy worlds that reality is catching up with today, who is creating the fantasy worlds of tomorrow?
Maçães thinks the answer is Silicon Valley, which he describes as “a fantasy land where engineering talent and capital come together to power the serious project of creating new worlds out of nothing”. It’s one of the most idiosyncratic descriptions of how startups work that I have read. VCs are the new Hollywood studios; founders are the directors and actors.
A founder’s job is essentially to create the most compelling narrative of what their company will look like in 10 to 20 years time. It’s not lying, it’s telling pre-truths. Being contrarian just means that you came up with a novel fantasy plot no one else had thought of yet.
Sometimes founders are able to re-create the fantasy narratives of their pitch decks. Sometimes you end up with Theranos.
And even when you do end up with Theranos, at least you get material for an exciting new Netflix series. Perhaps VCs should buy the movie rights to the startups they invest in as a hedge against their biggest portfolio failures?
The concept of the tech industry as a creator of fantasy worlds immediately reminded me of a conversation I had with my friend Max recently. His theory is that it’s not the lack of tech talent or venture capital that explains why Europe hasn’t been able to create a tech ecosystem on par with the US. It’s the absence of religiosity that has kept Europe from creating its own Google or Facebook. The US is able to create larger companies because it’s able to believe in larger and more ambitious narratives.
Silicon Valley is not just creating new fantasy worlds, it is building tools that allow others to create their own fantasy worlds. Enter social media.
If TV has taught us to think of ourselves as characters in the story of our lives, then social media has allowed us to actually write and edit the script and build fictional characters. Social media is essentially the democratization of virtual world building.
As I wrote in Signaling-as-a-Service, Twitter, Snapchat and Facebook are just massive virtual status arenas that allow us to build social capital through signaling. Some of that social capital might be built on top of real stories and actual achievements, but most of it is not based on reality. Every time you are applying an Instagram filter, you are already changing reality.
It’s not just that we bend reality in our social media narratives, we also play different characters. As Chris Poole already pointed out years ago, we all have multiple (online) identities. There is not just one reflection of yourself – identity is prismatic. Twitter-Julian (armchair intellectual) is not the same as Instagram-Julian (hobby photographer) or Facebook-Julian (high-school drinking buddy). Google Circles and Facebook Lists always got this wrong: They let us change who we shared with, but not who we shared as.
This is why social networking is not a winner-take-all market. We need different channels for our different, contradicting online personas.
The problem is not that we live in multiple realities or that these realities are sometimes at odds with each other. What’s problematic is that we sometimes get so immersed in one virtual world, that we forget about all the other realities – which brings us back to the problem of online conspiracies.
When I say proof-of-work, I’m not talking about consensus algorithms like the ones that some crypto currencies use. I’m talking about social networks.
At their core, social networks are primarily about one thing: Building social capital through signaling. As I wrote in Signaling as a Service, signaling can be broken down into three different components:
Signaling Message A hidden status subtext you’re trying to convey about yourself
Signaling Distribution The channel through which you’re communicating your signaling message
Signaling Amplification Ways to boost your signaling message to compete against status rivals
For example: A Patagonia vest signals both a prosocial attitude (“I care about the environment“) as well as wealth (“I can afford to spend $500 on a jacket“). Depending on where you live, it might also signal something about your occupation.
In order to signal these messages to others and build actual social capital you need a signaling distribution channel. One option would be to wear the vest in public where others can see it – but there are obvious physical constraints to the size of the audience you’d be able to reach.
This is where social networks come in.
Their primary role is to distribute signaling messages at scale and transform them into quantifiable social capital (in the form of likes and followers).
As social networks grow, they increase the potential reach of your signaling messages – but they also get crowded with status rivals. This is why social networks typically provide you with a set of signaling amplification tools. These tools help you boost your signaling messages and stand out from the crowd.
Almost every social network of note had an early signature proof of work hurdle. For Facebook it was posting some witty text-based status update. For Instagram, it was posting an interesting square photo. For Vine, an entertaining 6-second video. For Twitter, it was writing an amusing bit of text of 140 characters or fewer. Pinterest? Pinning a compelling photo. You can likely derive the proof of work for other networks like Quora and Reddit and Twitch and so on. Successful social networks don’t pose trick questions at the start, it’s usually clear what they want from you.
But the more I think about it, the less I like the comparison. I actually think that Eugene’s proof-of-work theory only scratches the surface of what social networks actually do.
Let me explain.
02 A closer look at proof mechanisms
Take a look at this very cliché Instagram picture. The photographer clearly put a lot of thought and effort into its composition and applied different filters and editing tools to make it look nicer.
It’s a perfect example of Eugene’s definition of proof-of-work. Proof-of-creative-work, to be more exact.
Editing your photo helps to amplify your signaling message and sets you apart within Instagram’s status arena (aka the newsfeed). It also adds additional signaling messages to your post: “Look how great a photographer I am” or “I’m a creative person”.
But those are not the main signaling messages you are communicating here. What you really want to tell your followers with this photo is something along the lines of “I’m a world-traveler” and “I’m in a happy relationship”(which in turn are also just signaling proxies for wealth and mating worthiness).
The photo and the location tag are your proof points.
Social networks are therefore not only signaling distribution (and amplification) networks – they also allow users to prove their signaling messages.
The creative proof-of-work is just pretext and helps to boost your post. What’s more important are the additional proof mechanisms that social networks provide. In the case of Instagram those are photos and location tags.
Instagram is essentially “pics or it didn’t happen”-as-a-service.
03 Implications for new social networks
When new social networks emerge they have to introduce new proof mechanisms to differentiate themselves from existing incumbents. These can either be novel proof-of-creative-work hurdles or completely new proof-of-x mechanisms.
TikTok is a good example for proof-of-creative-work innovation. The app provides creators with a powerful set of video editing tools that have opened a whole new level of creativity.
The cost to participate in TikTok’s status game is a lot higher than Instagram’s (compare a well-made dance choreography on TikTok to your median Instagram travel post) – but its powerful feed algorithms also make discovery easier and thus reward users faster and with more social capital.
TikTok doesn’t add any new proof points beyond its novel creative work hurdle though. You can signal and prove your creativity but you could achieve the same by uploading your video to Instagram.
Strava, on the other hand, introduced an entirely new proof mechanism: Proof-of-physical-activity. By using your phone’s GPS sensor (or a 3rd-party fitness tracker), users can actually prove how much and fast they ran or cycled. In contrast to Instagramphotos, Strava’s proof mechanism is a lot harder to fake (though there are exceptions).
What’s great about Strava is that it reinforces a behavior that’s actually good for you: While the status game that initially got you into the app might be zero sum, the actual physical exercise you have to put in to compete has a very positive, compounding effect.
The question is: What other social networks should we build that could have similar positive feedback loops? And what are their proof mechanisms?
I love the idea of a Strava for Cooking – but I’m very skeptical that it can be built. Why? Because the necessary proof mechanisms don’t exist.
The primary metric you optimize on when cooking is taste. But how would you measure or quantify taste? The closest proxy to taste that we have is optics: How good does the meal that you cooked look? This can easily be proved with a photo .. but that’s a proof-of-work mechanism that Instagram already offers (including filters to make your food look nicer). As long as no one comes up with a better proof mechanism for cooking, I think it’s unlikely that we will see a successful social network in the space.
I’m more optimistic about Strava for Learning.
While the activity of learning itself might be hard to quantify, you can measure the outcome of learning: knowledge. Has anyone built a multiplayer version of Anki yet? Flash cards would be a perfect proof-of-knowledge mechanism and could easily be turned into a game where you compete against friends.
A related product I’d love to see is Strava for Reading. Imagine an eBook reader that not only tracks how much time you spend reading but also *what* you are reading. Based on these proof-of-(reading)-work mechanisms you could build streaks or GitHub-contributions-like visualizations that incentivize users to read more (and more regularly).
You could even build leaderboards for different topics based on the content of the books and articles you read. Or think about a score that indicated how balanced your reading behavior per topic was (to incentivize users to read takes on political topics from different perspectives).
(Side note: Amazon’s monopoly on books might be the most underrated sub-optimal equilibrium in tech.)
Another app that would be interesting is a social investing app. Think “Robinhood but as a social network”. It seems like investing is already quite a social activity – just look at communities like r/wallstreetbets. As patio11 pointed out, Robinhood already feels more like a game than a finance app.
So why not build an investing app that opens with a feed of all your friends’ investments and their returns over time? Instead of sharing screenshots on Reddit and Instagram you could prove your investments right in the app.
Note that an app like this would not be about signaling wealth. It’s about signaling being right and the ability to prove it. This is probably an even stronger and more engaging mechanism than signaling wealth – and the reason why I’m still bullish on prediction markets.
Perhaps a well-designed, consumer-friendly prediction market app would be the ultimate proof-of-x social network. Strava for being right.
05 A Closing Ask
While we are on the topic of being right: Do you agree with my thoughts in this post? What other social networks and proof-of-x mechanisms would you like to see?