"What are the functionalities of this sort of network? Look, here's an interesting functionality. Suppose I think about random node failures. So suppose nodes on the internet are gonna fail randomly. Well most nodes are connected to very few. Most nodes are over here. So that means if you have random failure, this node is gonna be incredibly robust. So no one said, hey, let's. Make connections in such a way that makes the internet robust, but the fact that it emerges from the structure of the network. What about targeted failures? What if you want to shut down internet? What if you want to target failure, then you go after these, lots and lots of connections. So although the internet is really robust in handling failure but it's not at all robust to targeted failure. That's a functionality that emerges from the preferential [inaudible] rule. Nobody built them in. They just happened. So what have we learned? We learned that it's sort of fun to talk about networks. There's pictures but we can really unpack it in a formal way by constructing models and networks. Cause models and networks can focus on the logic. How does the network form. The structure. What are the statistical properties within networks? And then finally the functionality. What does the network do? Right. Does the network robust to random failures or is it robust to strategic failures? Does it give us six degrees of separation or 400 degrees of separation? Is it connected or non-connected? So there's all these functionalities that emerge from the network structure. And the network structure in turn is a result of. The individual logic for how people make connections, or how firms make connections, or how. " - Transcript from Scott Page Coursera
Scott Page Model Thinking MOOC Course