We, scientists, love the word “hierarchy.” In every professor, it evokes a picture of us chalking up a pyramid on the blackboard and confidently explaining, “at the top, we have the …” Hierarchies are systematic and meaningful orderings. They are the successful ends of research projects, and bringers of peace to our curious minds. They […]
The art, sport and science of network-epidemic algorithms
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 […]
Petter Holme 