3 rules for creating a network state

via a detour into self-assembly of teams

If you came just to read the rules and don't care too much about the research, scroll to the bottom. No hard feelings.

I set out to write a guide on how to form successful web3 teams. It was inspired by reading Loonshots, which resurfaced old research I came across on how different teams form, may it be science, open-source software or massive multi player online games teams. I convinced myself I had it all together, and only needed to copy-paste notes to form a coherent article. GPT would clean it up for me. I'll finish it with an analysis of the Farcaster ecosystem as a good enough proof of my thesis.

I sat down this morning at my favorite little Italian coffee place (€0.90 cents for an espresso macchiato) with the intent to write the draft. I got distracted by a truck, which for five minutes, tried to turn from the alley-way into the narrow street. Further a meter, back 80 cm it went. It looked like an impossible task thanks to little poles on each side of the footpath walk to stop pedestrians (aka tourists) from flâneur-ing* onto the street. This turned a somewhat awkward maneuver into a pain in the ass. 

Why do I tell you this? Because writing this story - where I thought I had it all figured out - felt like what the truck tried to do: A bit forward, a bit backward. But not really making it. No WAGMI.

Just like the truck, my words didn't really flow. The story wasn't there. I lied to myself! So here I am, the end of my workday, and still unsure about what I want you to take away from the research on team assembly, and how it relates to forming innovative teams working in web3.

What you'll get if you keep reading

I'll dive into the research on team assembly, doing a couple of side quests into open-source software teams to end up with three rules for building a network state. Hope you enjoy. 

What does Web3 and Oncofertility have in common?

You can't talk about team assembly without talking about networks. Or at least I can't. That's because teams have people who need to coordinate with each other. Boom! You have a network of prior and current relationships that - if they are optimized - result in a successful team.

As networks were central to this piece, I made little graphs to visualize the research. But how do you visualize in a static image that global closure is more important than local brokerage? And I wasn't ready to make a video or even a gif. Just look at them? A bad attempt to explain the concepts. 

Try 1 at explaining relational effects on team formation

I dismissed the most straightforward part as not worthy of my energy: Personal characteristics that influence team assembly like H-index (a measure of reputation in science) or prestige of affiliation, aka employer. 

Side quest 1: By the way, this is similar for open source software teams: Working with very reputable people boosts a developer's chances to multiply their reputation score, but reputable developers prefer to work with those with a similar high reputation level. Thus, there is a glass ceiling you can break if you have the right relationships (read the research paper).

This brings us to the second level of factors that influence team formation: Relationships. And not the type advertised on Unlonely's Dating on-chain show.

Preferential attachment matters in science. This is a fancy word for the observable behavior that everyone wants to work with influential people, those who are known by everyone else. It's the typical curve with the long tail: A few people have a lot of connections, and many people have hardly any. This means those influential people can pick with whom to form a company.

An image of a long tail graph

Side quest 2: H-index (scientist reputation) and preferrential attachment are not the same, but very closely related. H-index is a measure of how often your articles are cited. It's a measure of prestige. It's describing a person. Preferrential attachment is to network scientists what followers are to social media influencers. It's the number of people who a person is connected to. For scientists this means the number of people with whom you collaborated on a successful grant or published paper. Because failures are hidden away from the public eye. 

Far more interesting than preferential attachment, is that successful science teams are often formed with friends of friends. Or more accurately collaborators of collaborators. 

Again, your social capital matters! With whom you participate during a hackathon matters. With whom you chat at side events or on Farcaster matters. Your relationship matters. And ceteris paribus, they count more than your expertise and skills. Friends of friends lead to successful science teams because the middle person vouched for both parties. 

The role of the middle person is simply to bring two people together, and then they can leave them to it -whatever it is, just like in the "olden times" when your friends hooked you up with someone. The middle person injects trust into the relationship.

What does that mean for you? First, keep your connections alive. It's easy: Out of sight, out of mind. Use a system to help your brain. Don't be like me and build 90% of the system, and then don't turn on the notification.

Now to the most exciting: The network level aka ecosystem aka industry. I have to introduce an assumption before diving into the results. To be innovative, you need information asymmetry: You need to know things other people don't. You can achieve this by studying or being connected to a unique set of people. For a team to be innovative and, thanks to this, capture the market with their fantastic product, every team member should be connecting to different people. You don't want that A and B both know C. And for sure, you don't want teams with overlapping team memberships. 

Side quest 3: I'll pause here and clarify that scientists typically work on several research projects in overlapping areas. You never do only one project, but you are part of several teams simultaneously where each research project is at a different stage. Your collaborators become your competitors (for grant money) and turn again into your collaborators a couple of years later. And of course, your collaborators are employed at different universities, being nudged with other incentives.

Imagine you work in this new industry. The outcome of this industry is not clear. What works when for whom isn't clear. The people in this industry have the intuition that they are onto something big but no data to prove it. It's too early; everything is emerging. In such a setting, betting on different directions by being on different teams with no overlap between team members is the best way forward. You want every team to make a unique bet, hoping one of them will be correct (before the money runs out). Logical?

But, research on successful teams in Oncofertility didn't show this. Oncofertility was a new research field in the early 2000s, investigating fertility of cancer patients. On the contrary, it showed that some closure, i.e., overlap between teams, existed at the ecosystem level. The researchers speculated that the field is too new, too risky, too unknown to make different bets. You need overlap between teams to create trust in the method (technology) and each other.

Trying to visualize ecosystem effects on team formation

There was an external event that shocked the Oncofertility science field. Okay, shock is too harsh, but it changed how teams formed. In 2006/2007, the National Institute of Health created the Oncofertility Consortium. While this made funding easier, it reduced the impact ecosystem properties had on team formation. This raises the question of how regulation impacts an industry and the creation of successful teams in it. But that's a story for another post.

Back to the heading: How to build a network state. Here are three rules: 

Rule 1: Build it with the friends of your friends. Talk about what you are doing with your friends, who might bring it up when they talk with their friends, and someone will be interested in working with you.

Rule 2: Have a well-connected person. They'll be a magnet for other people to join. And for funding.

Rule 3: Work with other groups. Whatever you have in mind, I'm sure someone is thinking about a similar idea. Instead of competing, collaborate. Talk with each other, and exchange ideas and strategies. You know the saying that you'll go further with someone. Ensure you have at least one person whose main task is stimulating and keeping this collaboration alive. They will be your bridge builder, project champion, and gate to new ideas and resources. You can also call them your weaver, bringing all the strands together.

*The french word Flâneur describes a person who has no hurry in the world and can stroll around at their own pleasure. The word strolling just didn't fit the feeling I wanted to express. Hence the French-English combination of flâneuring. Saunterer doesn't have the same ring to it, it sounds too energetic.

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#science#network state#social networks
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