Reproduce “Layer Communities in Multiplex Networks” on OpenResearch
Turn your favorite coding agents into research agents that review literature, develop hypotheses, and run experiments.
Universal app for Apple silicon and Intel. Requires macOS 11 or later.
About this paper
Ta-Chu Kao, Mason A. Porter
Kao and Porter introduce a method for grouping layers in multiplex networks by similarity. It compares the overlap of edges between layer pairs, averages node-level scores, and clusters the resulting layer-similarity network; edge weights are ignored. In a 37-airline data set, its partition agrees with a country-or-region benchmark at NMI 0.83, versus 0.42 for mesoscopic similarity, while Jaccard reaches 0.81.
Summary by alphaXiv.
Tip: change arxiv.org to autoarxiv.org in any arXiv abstract link to open the paper here.