dorsal/arxiv
View SchemaWeighted Assortative And Disassortative Networks Model
| Authors | C. C. Leung, H. F. Chau |
|---|---|
| Categories | |
| ArXiv ID | physics/0607134 |
| URL | https://arxiv.org/abs/physics/0607134 |
| DOI | 10.1016/j.physa.2006.12.022 |
Abstract
Real-world networks process structured connections since they have non-trivial vertex degree correlation and clustering. Here we propose a toy model of structure formation in real-world weighted network. In our model, a network evolves by topological growth as well as by weight change. In addition, we introduce the weighted assortativity coefficient, which generalizes the assortativity coefficient of a topological network, to measure the tendency of having a high-weighted link between two vertices of similar degrees. Network generated by our model exhibits scale-free behavior with a tunable exponent. Besides, a few non-trivial features found in real-world networks are reproduced by varying the parameter ruling the speed of weight evolution. Most importantly, by studying the weighted assortativity coefficient, we found that both topologically assortative and disassortative networks generated by our model are in fact weighted assortative.
{
"annotation_id": "3121acf4-9fe2-464c-8762-8575d0662a1c",
"date_created": "2026-03-02T18:01:10.913000Z",
"date_modified": "2026-03-02T18:01:10.913000Z",
"file_hash": "1f4af16a2e4addcda8b998c3ac1834c392e6852ce0d6746f82f44b46e6af46ac",
"private": false,
"record": {
"abstract": "Real-world networks process structured connections since they have\nnon-trivial vertex degree correlation and clustering. Here we propose a toy\nmodel of structure formation in real-world weighted network. In our model, a\nnetwork evolves by topological growth as well as by weight change. In addition,\nwe introduce the weighted assortativity coefficient, which generalizes the\nassortativity coefficient of a topological network, to measure the tendency of\nhaving a high-weighted link between two vertices of similar degrees. Network\ngenerated by our model exhibits scale-free behavior with a tunable exponent.\nBesides, a few non-trivial features found in real-world networks are reproduced\nby varying the parameter ruling the speed of weight evolution. Most\nimportantly, by studying the weighted assortativity coefficient, we found that\nboth topologically assortative and disassortative networks generated by our\nmodel are in fact weighted assortative.",
"arxiv_id": "physics/0607134",
"authors": [
"C. C. Leung",
"H. F. Chau"
],
"categories": [
"physics.soc-ph"
],
"doi": "10.1016/j.physa.2006.12.022",
"title": "Weighted Assortative And Disassortative Networks Model",
"url": "https://arxiv.org/abs/physics/0607134"
},
"schema_id": "dorsal/arxiv",
"source": {
"execution_id": "937cd02d-f31c-46a0-8cef-10b76c77656f",
"id": "arXiv Dataset IDs",
"type": "Model",
"variant": "snapshot-2026-03-01",
"version": "0.1.0"
},
"user_id": 1000002
}