Multi-level Graph Drawing using Infomap Clustering

TL;DR

This paper introduces a multi-level graph drawing method that leverages Infomap clustering to improve visualization quality of large networks, demonstrating significant performance benefits.

Contribution

It combines Infomap clustering with multi-level graph drawing to enhance visualization quality for large, complex networks.

Findings

Improved visualization quality metrics.

Effective handling of large network structures.

Fast algorithm performance in practice.

Abstract

Infomap clustering finds the community structures that minimize the expected description length of a random walk trajectory; algorithms for infomap clustering run fast in practice for large graphs. In this paper we leverage the effectiveness of Infomap clustering combined with the multi-level graph drawing paradigm. Experiments show that our new Infomap based multi-level algorithm produces good visualization of large and complex networks, with significant improvement in quality metrics.