igraph 2.0.0

The igraph R package has reached version 2.0.0.

  • June 13th, 2024

Collapsing a bipartite co-occurrence network

This note is a follow-up to the previous one. It shows how to use student-submitted keywords to find clusters of shared interests between the students.

  • September 16th, 2016

Turning keywords into a co-occurrence network

This note is addressed to the GLM Fall 2016 students who are currently taking my Statistical Reasoning and Quantitative Methods course at Sciences Po in Paris.

  • September 10th, 2016

An awesome list of network analysis resources

Inspired by the awesome R list that I mentioned a few months ago, I have started the awesome-network-analysis list, which features a large section on R packages.

  • April 11th, 2016

ggnetwork: Network geometries for ggplot2

This note is a ~~shameless plug~~ demo of the ggnetwork package, which provides several geoms to plot network objects with ggplot2, and which just got published on CRAN. See the package vignette for a more detailed guide to its functionalities.

  • March 28th, 2016

Exponential random graph models with R

This note documents the small but growing microverse of R packages on CRAN to produce various forms of exponential random graph models (ERGMs), which are a kind of modelling strategy akin to logistic regression for dyadic data.

  • February 6th, 2016

From networkx to igraph

This note translates the code from an interesting blog post (in French) from Python to R. The code includes a function to compute closeness vitality with the igraph package.

  • October 31st, 2015

Visualizing networks with ggplot2

This note describes a few ways to handle network objects (which might be objects of class igraph or network, or data frames representing edge lists) through graphical methods that rely on ggplot2.

  • October 5th, 2015

Serrano et al.'s disparity filter algorithm for directed networks

The disparity filter algorithm by Serrano et al. is a network reduction technique to identify the ‘backbone’ of a weighted network. This note explains how to implement the algorithm in full, based on existing implementations and on Serrano et al.'s paper.

  • October 2nd, 2015

Weighting co-authorship networks

This note explains how to implement two edge weighting schemes that are relevant to co-authorship networks, based on my work on legislative cosponsorship networks.

  • September 18th, 2015

Working with R network objects

Here are a few things that I have learnt while working with R network objects, using the igraph and network + sna packages (the last two packages go well together).

  • September 17th, 2015