Generating bipartite networks with a prescribed joint degree distribution. Boroojeni, A. A., Dewar, J., Wu, T., & Hyman, J. M Journal of Complex Networks, 5(6):839–857, December, 2017. 15 citations (Semantic Scholar/DOI) [2025-10-11] 11 citations (Crossref/DOI) [2025-02-03]![Generating bipartite networks with a prescribed joint degree distribution [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex We describe a class of new algorithms to construct bipartite networks that preserves a prescribed degree and joint-degree (degree–degree) distribution of the nodes. Bipartite networks are graphs that can represent real-world interactions between two disjoint sets, such as actor–movie networks, author–article networks, co-occurrence networks and heterosexual partnership networks. Often there is a strong correlation between the degree of a node and the degrees of the neighbours of that node that must be preserved when generating a network that reflects the structure of the underling system. Our bipartite $2K$ ($B2K$) algorithms generate an ensemble of networks that preserve prescribed degree sequences for the two disjoint set of nodes in the bipartite network, and the joint-degree distribution that is the distribution of the degrees of all neighbours of nodes with the same degree. We illustrate the effectiveness of the algorithms on a romance network using the NetworkX software environment to compare other properties of a target network that are not directly enforced by the $B2K$ algorithms. We observe that when average degree of nodes is low, as is the case for romance and heterosexual partnership networks, then the $B2K$ networks tend to preserve additional properties, such as the cluster coefficients, than algorithms that do not preserve the joint-degree distribution of the original network.
@article{boroojeni_generating_2017,
title = {Generating bipartite networks with a prescribed joint degree distribution},
volume = {5},
issn = {2051-1310},
url = {https://doi.org/10.1093/comnet/cnx014},
doi = {10.1093/comnet/cnx014},
abstract = {We describe a class of new algorithms to construct bipartite networks that preserves a prescribed degree and joint-degree (degree–degree) distribution of the nodes. Bipartite networks are graphs that can represent real-world interactions between two disjoint sets, such as actor–movie networks, author–article networks, co-occurrence networks and heterosexual partnership networks. Often there is a strong correlation between the degree of a node and the degrees of the neighbours of that node that must be preserved when generating a network that reflects the structure of the underling system. Our bipartite \$2K\$ (\$B2K\$) algorithms generate an ensemble of networks that preserve prescribed degree sequences for the two disjoint set of nodes in the bipartite network, and the joint-degree distribution that is the distribution of the degrees of all neighbours of nodes with the same degree. We illustrate the effectiveness of the algorithms on a romance network using the NetworkX software environment to compare other properties of a target network that are not directly enforced by the \$B2K\$ algorithms. We observe that when average degree of nodes is low, as is the case for romance and heterosexual partnership networks, then the \$B2K\$ networks tend to preserve additional properties, such as the cluster coefficients, than algorithms that do not preserve the joint-degree distribution of the original network.},
number = {6},
urldate = {2025-02-03},
journal = {Journal of Complex Networks},
author = {Boroojeni, Asma Azizi and Dewar, Jeremy and Wu, Tong and Hyman, James M},
month = dec,
year = {2017},
note = {15 citations (Semantic Scholar/DOI) [2025-10-11]
11 citations (Crossref/DOI) [2025-02-03]},
pages = {839--857},
}
Downloads: 0
{"_id":"N5xZCnAaC2cDqpC4X","bibbaseid":"boroojeni-dewar-wu-hyman-generatingbipartitenetworkswithaprescribedjointdegreedistribution-2017","author_short":["Boroojeni, A. A.","Dewar, J.","Wu, T.","Hyman, J. M"],"bibdata":{"bibtype":"article","type":"article","title":"Generating bipartite networks with a prescribed joint degree distribution","volume":"5","issn":"2051-1310","url":"https://doi.org/10.1093/comnet/cnx014","doi":"10.1093/comnet/cnx014","abstract":"We describe a class of new algorithms to construct bipartite networks that preserves a prescribed degree and joint-degree (degree–degree) distribution of the nodes. Bipartite networks are graphs that can represent real-world interactions between two disjoint sets, such as actor–movie networks, author–article networks, co-occurrence networks and heterosexual partnership networks. Often there is a strong correlation between the degree of a node and the degrees of the neighbours of that node that must be preserved when generating a network that reflects the structure of the underling system. Our bipartite $2K$ ($B2K$) algorithms generate an ensemble of networks that preserve prescribed degree sequences for the two disjoint set of nodes in the bipartite network, and the joint-degree distribution that is the distribution of the degrees of all neighbours of nodes with the same degree. We illustrate the effectiveness of the algorithms on a romance network using the NetworkX software environment to compare other properties of a target network that are not directly enforced by the $B2K$ algorithms. We observe that when average degree of nodes is low, as is the case for romance and heterosexual partnership networks, then the $B2K$ networks tend to preserve additional properties, such as the cluster coefficients, than algorithms that do not preserve the joint-degree distribution of the original network.","number":"6","urldate":"2025-02-03","journal":"Journal of Complex Networks","author":[{"propositions":[],"lastnames":["Boroojeni"],"firstnames":["Asma","Azizi"],"suffixes":[]},{"propositions":[],"lastnames":["Dewar"],"firstnames":["Jeremy"],"suffixes":[]},{"propositions":[],"lastnames":["Wu"],"firstnames":["Tong"],"suffixes":[]},{"propositions":[],"lastnames":["Hyman"],"firstnames":["James","M"],"suffixes":[]}],"month":"December","year":"2017","note":"15 citations (Semantic Scholar/DOI) [2025-10-11] 11 citations (Crossref/DOI) [2025-02-03]","pages":"839–857","bibtex":"@article{boroojeni_generating_2017,\n\ttitle = {Generating bipartite networks with a prescribed joint degree distribution},\n\tvolume = {5},\n\tissn = {2051-1310},\n\turl = {https://doi.org/10.1093/comnet/cnx014},\n\tdoi = {10.1093/comnet/cnx014},\n\tabstract = {We describe a class of new algorithms to construct bipartite networks that preserves a prescribed degree and joint-degree (degree–degree) distribution of the nodes. Bipartite networks are graphs that can represent real-world interactions between two disjoint sets, such as actor–movie networks, author–article networks, co-occurrence networks and heterosexual partnership networks. Often there is a strong correlation between the degree of a node and the degrees of the neighbours of that node that must be preserved when generating a network that reflects the structure of the underling system. Our bipartite \\$2K\\$ (\\$B2K\\$) algorithms generate an ensemble of networks that preserve prescribed degree sequences for the two disjoint set of nodes in the bipartite network, and the joint-degree distribution that is the distribution of the degrees of all neighbours of nodes with the same degree. We illustrate the effectiveness of the algorithms on a romance network using the NetworkX software environment to compare other properties of a target network that are not directly enforced by the \\$B2K\\$ algorithms. We observe that when average degree of nodes is low, as is the case for romance and heterosexual partnership networks, then the \\$B2K\\$ networks tend to preserve additional properties, such as the cluster coefficients, than algorithms that do not preserve the joint-degree distribution of the original network.},\n\tnumber = {6},\n\turldate = {2025-02-03},\n\tjournal = {Journal of Complex Networks},\n\tauthor = {Boroojeni, Asma Azizi and Dewar, Jeremy and Wu, Tong and Hyman, James M},\n\tmonth = dec,\n\tyear = {2017},\n\tnote = {15 citations (Semantic Scholar/DOI) [2025-10-11]\n11 citations (Crossref/DOI) [2025-02-03]},\n\tpages = {839--857},\n}\n\n\n\n","author_short":["Boroojeni, A. A.","Dewar, J.","Wu, T.","Hyman, J. M"],"key":"boroojeni_generating_2017","id":"boroojeni_generating_2017","bibbaseid":"boroojeni-dewar-wu-hyman-generatingbipartitenetworkswithaprescribedjointdegreedistribution-2017","role":"author","urls":{"Paper":"https://doi.org/10.1093/comnet/cnx014"},"metadata":{"authorlinks":{}},"downloads":0,"html":""},"bibtype":"article","biburl":"https://bibbase.org/zotero/hegera","dataSources":["MjyMYAXhzMT5PBaZ2"],"keywords":[],"search_terms":["generating","bipartite","networks","prescribed","joint","degree","distribution","boroojeni","dewar","wu","hyman"],"title":"Generating bipartite networks with a prescribed joint degree distribution","year":2017}