Daniel Steinbock

The question may have never occured to network researchers and enthusiasts. When you’ve found a paradigm that you love, it’s hard to see the boundaries of its utility. It’s the old “when you have a hammer, everything looks like a nail” story. But actually, the question which titles this post is an important networks question — not just a caution against overzealous methodologizing — because knowing when the network doesn’t matter means knowing when it does.

Network analysts use random networks as the standard by which to measure order in the networks they study. That’s because a random network is the graph-theoretic way of saying structure doesn’t matter. If the network structure you’re studying is significantly different from the random net, most likely it can’t be explained by chance alone; it has order, pattern, maybe even complexity. In other words, for the purposes of studying whatever system produced that structure, the network matters, i.e. it’s worth paying attention to.

And in the games of life and science, what matters most is knowing what is worthy of your thought and attention, and what is not.