Reconstructing Mesoscale Network Structures
dc.contributor.author | Van Lidth De Jeude, J | |
dc.contributor.author | Di Clemente, R | |
dc.contributor.author | Caldarelli, G | |
dc.contributor.author | Saracco, F | |
dc.contributor.author | Squartini, T | |
dc.date.accessioned | 2020-01-29T09:24:25Z | |
dc.date.issued | 2019-01-10 | |
dc.description.abstract | When facing the problem of reconstructing complex mesoscale network structures, it is generally believed that models encoding the nodes organization into modules must be employed. The present paper focuses on two block structures that characterize the empirical mesoscale organization of many real-world networks, i.e., the bow-tie and the core-periphery ones, with the aim of quantifying the minimal amount of topological information that needs to be enforced in order to reproduce the topological details of the former. Our analysis shows that constraining the network degree sequences is often enough to reproduce such structures, as confirmed by model selection criteria as AIC or BIC. As a byproduct, our paper enriches the toolbox for the analysis of bipartite networks, still far from being complete: both the bow-tie and the core-periphery structure, in fact, partition the networks into asymmetric blocks characterized by binary, directed connections, thus calling for the extension of a recently proposed method to randomize undirected, bipartite networks to the directed case. | en_GB |
dc.description.sponsorship | EU | en_GB |
dc.description.sponsorship | EU | en_GB |
dc.description.sponsorship | EU | en_GB |
dc.description.sponsorship | EU | en_GB |
dc.description.sponsorship | EU | en_GB |
dc.description.sponsorship | Newton International Fellowship | en_GB |
dc.description.sponsorship | The Royal Society | en_GB |
dc.description.sponsorship | The British Academy | en_GB |
dc.description.sponsorship | Academy of Medical Sciences | en_GB |
dc.identifier.citation | Vol. 2019, article 5120581 | en_GB |
dc.identifier.doi | 10.1155/2019/5120581 | |
dc.identifier.grantnumber | 676547 | en_GB |
dc.identifier.grantnumber | 640772 | en_GB |
dc.identifier.grantnumber | 317532 | en_GB |
dc.identifier.grantnumber | 687941 | en_GB |
dc.identifier.grantnumber | 654024 | en_GB |
dc.identifier.grantnumber | NF170505 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/40620 | |
dc.language.iso | en | en_GB |
dc.publisher | Hindawi | en_GB |
dc.relation.url | http://comtrade.un.org/ | en_GB |
dc.rights | © 2019 Jeroen van Lidth de Jeude et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. | en_GB |
dc.title | Reconstructing Mesoscale Network Structures | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2020-01-29T09:24:25Z | |
dc.identifier.issn | 1076-2787 | |
dc.description | This is the final version. Available from Hindawi via the DOI in this record. | en_GB |
dc.description | World Trade Web data that support the findings of this study are openly available at the UN Comtrade Database (http://comtrade.un.org/). Dutch interbank exposures data are not publicly available due to privacy restrictions. | en_GB |
dc.identifier.journal | Complexity | en_GB |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_GB |
dcterms.dateAccepted | 2018-12-19 | |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2018-12-19 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2020-01-29T09:17:49Z | |
refterms.versionFCD | VoR | |
refterms.dateFOA | 2020-01-29T09:24:28Z | |
refterms.panel | B | en_GB |
refterms.depositException | publishedGoldOA |
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Except where otherwise noted, this item's licence is described as © 2019 Jeroen van Lidth de Jeude et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.