Pub Date : 2024-06-05DOI: 10.24072/pci.networksci.100113
Cédric Sueur
{"title":"Unveiling the Hidden Dynamics of Knowledge Graphs: The Role of Superficiality in Structuring Information","authors":"Cédric Sueur","doi":"10.24072/pci.networksci.100113","DOIUrl":"https://doi.org/10.24072/pci.networksci.100113","url":null,"abstract":"","PeriodicalId":497435,"journal":{"name":"Peer Community In Network Science","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141383322","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-08DOI: 10.24072/pci.networksci.100181
Remy Cazabet
{"title":"A theoretical and empirical evaluation of modularities for hypergraphs","authors":"Remy Cazabet","doi":"10.24072/pci.networksci.100181","DOIUrl":"https://doi.org/10.24072/pci.networksci.100181","url":null,"abstract":"","PeriodicalId":497435,"journal":{"name":"Peer Community In Network Science","volume":"12 17","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140257985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-22DOI: 10.24072/pci.networksci.100112
Steve Lawford
{"title":"An application of PCA to social networks and healthy ageing","authors":"Steve Lawford","doi":"10.24072/pci.networksci.100112","DOIUrl":"https://doi.org/10.24072/pci.networksci.100112","url":null,"abstract":"","PeriodicalId":497435,"journal":{"name":"Peer Community In Network Science","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140441253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-20DOI: 10.24072/pci.networksci.100114
Leto Peel
Network structure is often considered one of the most important features of a network, and various models exist to generate graphs having one of the most studied types of structures, such as blocks/communities or spatial structures. In this article, we introduce a framework for the generation of random graphs with a controlled size -- number of nodes, edges -- and a customizable structure, beyond blocks and spatial ones, based on node-pair rank and a tunable probability function allowing to control the amount of randomness. We introduce a structure zoo -- a collection of original network structures -- and conduct experiments on the small-world properties of networks generated by those structures. Finally, we introduce an implementation as a Python library named Structify-net.
{"title":"A model petting zoo for interacting with network structure","authors":"Leto Peel","doi":"10.24072/pci.networksci.100114","DOIUrl":"https://doi.org/10.24072/pci.networksci.100114","url":null,"abstract":"Network structure is often considered one of the most important features of a network, and various models exist to generate graphs having one of the most studied types of structures, such as blocks/communities or spatial structures. In this article, we introduce a framework for the generation of random graphs with a controlled size -- number of nodes, edges -- and a customizable structure, beyond blocks and spatial ones, based on node-pair rank and a tunable probability function allowing to control the amount of randomness. We introduce a structure zoo -- a collection of original network structures -- and conduct experiments on the small-world properties of networks generated by those structures. Finally, we introduce an implementation as a Python library named Structify-net.","PeriodicalId":497435,"journal":{"name":"Peer Community In Network Science","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136262994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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