The other day, four Québécois gentlemen put out an arxiv preprint about one of my favorite topics*—algorithms for network epidemiology. In this blog post, I will try to lure you into: (1) Reading their manuscript. (2) Thinking about network-epi algorithm design. (3) Using my code for SIR (and theirs for SIS). *As a problem-solving exercise, […]
Crazy fast code for SIR on temporal networks
Now I turned this blog post into a paper. This is a follow-up to my post a couple of days ago about all the nitty-gritty when coding up a compartmental model for empirical temporal networks. I guess the question lingering is: How do you do it then? There are a very straightforward way and an […]
Getting down to the brass tacks (of SIR on temporal networks)
Now I turned this blog post into an arXiv preprint: https://arxiv.org/abs/2007.14386 Here, I will discuss some technical issues of compartmental models in general, and the SIR model in particular, on temporal networks. These are things that feel a bit too off-topic to even bother readers of papers, but everyone into network epidemiology needs to consider […]
Ridiculograms: A ridiculous dialogue
If you’re a network scientist, or you’ve hung around with one, you’ve probably heard about ridiculograms. It’s a tongue-in-cheek derogative word for plots of huge networks intended to impress by their complexity. I have a vague memory of someone crediting Marc Vidal for coining it. In this blog post, we will explore if they really […]
Less is more
In this blog post, I will explore why network science is mostly a science of large networks and argue that studying small networks can be just as rewarding and challenging as studying large ones. In other words, a manifesto for small-network science. (But a modest one, because it is not going to be any main […]
How to be creative
This is not a shot at making a side career as a motivational speaker. There are, of course, tons of more creative people out there, and even science about it! Still, I couldn’t resist writing down my thoughts since I slightly disagree with some of the gurus out there. 😛 1. Be bored Good ideas […]
The mild identity crisis of computational social science
I really like computational social science and love to identify myself as a computational social scientist. Having an identity in that sense is perhaps not so important. Throughout my entire career, I’ve got accustomed to being a [one field] person doing [another field] things, and learned to like it. Still computational social science very much […]
Fastest network-SIR code in the East
Update May 12, 2020. Some people climb Mount Everest. I rewrote this code in Fortran. Update July 30, 2018. I just realized that it is not necessary to put the recovery events on the heap (stupid me). So, I took some time to seriously squeeze out most of this approach. You can find the code […]
Zachary’s Zachary karate club
If you haven’t heard about Zachary’s karate club, you should probably be careful calling yourself a network scientist in the wrong company. It is a small network data set that is used as an example and benchmark for community detection algorithms. It even has a club! The Zachary Karate Club Club. With a trophy going […]
Power-laws and me
A day or two ago, Anna Broido and Aaron Clauset arxived a paper about how rare scale-free networks really are. If network science was invented today, I think such an article would not raise many eyebrows. Now it already got much attention, and I think it looks like a methodologically solid and important contribution. To someone […]
Petter Holme 