[GSoC 2026] Interested in Community Detection Guide: introduction

1

Hi everyone,

I’m Jacopo, a third-year Mathematical Engineering student at Politecnico di Milano, with a focus on algorithms, graph theory, and probabilistic methods.

I’m interested in the Community Detection Guide mentored project for GSoC 2026.

I have hands-on experience with graph algorithms in Python: for a university project I built an AI for the Scotland Yard board game, modelling London’s transport network as a 199-node graph and implementing shortest-path search with resource constraints using NetworkX. That project gave me a strong intuition for how graph structure affects algorithm behavior in practice, exactly the kind of insight I’d want to communicate through a well-designed Jupyter notebook.

I’ve had a look at the igraph Python documentation and the existing tutorials. Is there a preferred way to get started as a contributor before the proposal deadline? A good first issue or a specific section of the docs that needs work would be very helpful.

Thanks,
Jacopo

2

Hello Jacopo,

I just saw this post after I noticed your PR.

It’s great to see your interest in igraph, and contributions are of course welcome. However, this year we are not participating in GSoC, simply because we do not have sufficient mentoring capacity at the moment. Personally I will not have the time to dedicate to GSoC this summer.

Could you please let me know where you found references to this project, so we can eliminate misunderstandings? I assume here? I will update that page to indicate what has already been completed and to make it clear that GSoC is not available for 2026.

The community detection guide was a project last year, which was completed, although it needs polish before it can be published. A draft is here. If you are interested, continued contributions to this guide are welcome (especially to help with publishing a finalized version), but we cannot make it a GSoC project this year.

I will have a look at your PR during the Easter holidays.