Straightness & Spatial graphs

3 December 2016

These scripts were designed to compute several variants of the Straightness (aka. Directness and probably other names): the ratio of the Euclidean to the graph distance. It is a measure designed to study spatial graphs, i.e. graphs embedded in a Euclidean space (nodes have spatial positions, links have spatial length, etc.). First, this toolbox can process the Straightness using the traditional approach, i.e. considering only paths connecting two nodes. It can process the Straightness between two specific nodes, or the Straightness averaged over certain pairs of nodes in the graph (possibly all of them). Second, this toolbox can also compute the average Straightness through a continuous approach (by opposition to the discrete traditional approach), and incidentally this is the point of the below article. URL: https://github.com/CompNet/SpatialMeasures Production date: 2016 Related publication:  Vincent Labatut. « Continuous Average Straightness in Spatial Graphs ». In : Journalof Complex Networks 6(2):269-296 (2018). DOI: 10.1093/comnet/cnx033. ⟨hal-01571212⟩

Opinion-based centrality measure for multiplex networks

3 December 2016

These scripts were designed for two purposes: Process the opinion centrality, a new centrality measure for multiplex networks. Compare it to other existing multiplex centrality measures. Our scripts were applied to a collection of multiplex networks obtained from public sources and provided in our GitHub project. The tool itself, the data and the experimental results are all described in the below article. URL: https://github.com/CompNet/MultiplexCentrality Production date: 2015–2016 Related publication:  Alexandre Reiffers et Vincent Labatut. « Opinion-based centrality in multiplexnetworks : A convex optimization approach ». In : Network Science 5(2):213-234 (2017). DOI: 10.1017/nws.2017.7. ⟨hal-01486629⟩  (cite this article if you use the software)

Generation and analysis of spatial graphs

2 December 2016

These scripts were designed to generate various types of spatial graphs, and compute certain topological properties. More precisely, the goal here is to study so-called orb-web networks, which mimic typical spider webs, with a focus on the straightness measure.