was fun! thanks!
By the way, I heard that you were taking photos during @9fe72c76 's presentation. I’ve also made a video excerpt of his talk. Since the presentation was in Japanese, feel free to ask me if you have any questions. I can ask him directly.👍 Also, feel free to ask about the presentations of the other speakers as well. 😉 https://youtu.be/Iitvil8bFGE
Ah yeah I saw “scale-free” network which caught my interest, since I remember reading up on that at one point.
What interests you specifically about scale-free networks? I may be able to help
I don't remember, I just remembered reading about it at one point
I think it may have been in the context of neural networks or something...
Ah ok, you don't have a specific need? Scale-free networks tend to occur in social networks (probably in Nostr too), so they're important to know about if you want to do network analysis on such a network
What does “scale-free” mean
In the context of a network, "scale-free" means that the degree distribution follows a power law. Degree distribution is math speak for "how many followers does a typical npub have", and a power law is a distribution with so-called fat tails, meaning that some npubs have a huge number of followers, BUT many npubs (the tail) have non-negligible numbers of followers to.