{"doi":"10.1093/comnet/cnac031","title":"Centrality measures in interval-weighted networks","abstract":"<jats:title>Abstract</jats:title>\n               <jats:p>Centrality measures are used in network science to assess the centrality of vertices or the position they occupy in a network. There are a large number of centrality measures according to some criterion. However, the generalizations of the most well-known centrality measures for weighted networks, degree centrality, closeness centrality and betweenness centrality have solely assumed the edge weights to be constants. This article proposes a methodology to generalize degree, closeness and betweenness centralities taking into account the variability of edge weights in the form of closed intervals (interval-weighted networks, IWN). We apply our centrality measures approach to two real-world IWN. The first is a commuter network in mainland Portugal, between the 23 NUTS 3 Regions. The second focuses on annual merchandise trade between 28 European countries, from 2003 to 2015.</jats:p>","journal":"Journal of Complex Networks","year":2022,"id":23352,"datarank":0.439538718638818,"base_score":2.0794415416798357,"endowment":2.0794415416798357,"self_citation_contribution":0.31191623125197543,"citation_network_contribution":0.12762248738684256,"self_endowment_contribution":0.31191623125197543,"citer_contribution":0.12762248738684256,"corpus_percentile":null,"corpus_rank":null,"citation_count":7,"citer_count":7,"citers_with_citation_signal":4,"citers_with_endowment":4,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":143661,"name":"Paula Brito","orcid":null,"position":1,"is_corresponding":false},{"id":143662,"name":"Pedro Campos","orcid":null,"position":2,"is_corresponding":false},{"id":143660,"name":"Hélder Alves","orcid":"0000-0001-8423-4653","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"base_score":2.0794415416798357,"endowment":2.0794415416798357,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"21071399","pmcid":null,"openalex_id":"https://openalex.org/W3174053386","authors":[],"funders":[{"funder_name":"Fundação para a Ciência e a Tecnologia, I.P.","grant_id":"UIDB/50014/2020","title":"INESC TEC- Institute for Systems and Computer Engineering, Technology and Science"},{"funder_name":"European Commission","grant_id":"825215","title":"A FINancial supervision and TECHnology compliance training programme"}],"total_grants":2,"fwci":0.6253,"citation_percentile":0.63891753,"influential_citations":1,"citation_trend":[{"year":2023,"count":1},{"year":2024,"count":3},{"year":2025,"count":1},{"year":2026,"count":2}],"oa_status":"closed","license":"OUP Standard Publication Reuse","oa_locations":[{"url":"http://arxiv.org/pdf/2106.10016","host_type":"GREEN"},{"url":"https://academic.oup.com/comnet/article-pdf/10/4/cnac031/45047219/cnac031.pdf","host_type":"publisher"},{"url":"https://doi.org/10.1093/comnet/cnac031","host_type":"journal"},{"url":"https://dx.doi.org/10.48550/arxiv.2106.10016","host_type":""},{"url":"http://arxiv.org/abs/2106.10016","host_type":""},{"url":"https://arxiv.org/abs/2106.10016","host_type":""}],"fields_of_study":["Complex Network Analysis Techniques","Graph theory and applications","Opinion Dynamics and Social Influence","Computer Science","Physics","Mathematics","0103 physical sciences","0202 electrical engineering, electronic engineering, information engineering","02 engineering and technology","01 natural sciences"],"mesh_terms":[],"keywords":["Centrality","Betweenness centrality","Closeness","Network theory","Katz centrality","Network science","Interval (graph theory)","Computer science","Position (finance)","Complex network","Mathematics","Statistics","Combinatorics","Business","Social and Information Networks (cs.SI)","FOS: Computer and information sciences","Physics - Physics and Society","FOS: Physical sciences","Computer Science - Social and Information Networks","Physics and Society (physics.soc-ph)"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Partnerships for the goals"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-06-07T19:14:51.104763Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}