{"id":"https://openalex.org/W3167820860","doi":"https://doi.org/10.1140/epjds/s13688-021-00287-6","title":"Competition-driven modeling of temporal networks","display_name":"Competition-driven modeling of temporal networks","publication_year":2021,"publication_date":"2021-06-03","ids":{"openalex":"https://openalex.org/W3167820860","doi":"https://doi.org/10.1140/epjds/s13688-021-00287-6","mag":"3167820860"},"language":"en","primary_location":{"id":"doi:10.1140/epjds/s13688-021-00287-6","is_oa":true,"landing_page_url":"https://doi.org/10.1140/epjds/s13688-021-00287-6","pdf_url":"https://epjdatascience.springeropen.com/track/pdf/10.1140/epjds/s13688-021-00287-6","source":{"id":"https://openalex.org/S2504380752","display_name":"EPJ Data Science","issn_l":"2193-1127","issn":["2193-1127"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EPJ Data Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://epjdatascience.springeropen.com/track/pdf/10.1140/epjds/s13688-021-00287-6","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5009692602","display_name":"Kaijie Zhu","orcid":"https://orcid.org/0000-0002-3235-188X"},"institutions":[{"id":"https://openalex.org/I4210091712","display_name":"Zhengzhou University of Science and Technology","ror":"https://ror.org/00b3j7936","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210091712"]},{"id":"https://openalex.org/I83019370","display_name":"Eindhoven University of Technology","ror":"https://ror.org/02c2kyt77","country_code":"NL","type":"education","lineage":["https://openalex.org/I83019370"]}],"countries":["CN","NL"],"is_corresponding":true,"raw_author_name":"Kaijie Zhu","raw_affiliation_strings":["NDSC, Zhengzhou, China","TU Eindhoven, Eindhoven, Netherlands"],"affiliations":[{"raw_affiliation_string":"NDSC, Zhengzhou, China","institution_ids":["https://openalex.org/I4210091712"]},{"raw_affiliation_string":"TU Eindhoven, Eindhoven, Netherlands","institution_ids":["https://openalex.org/I83019370"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019818981","display_name":"George Fletcher","orcid":null},"institutions":[{"id":"https://openalex.org/I83019370","display_name":"Eindhoven University of Technology","ror":"https://ror.org/02c2kyt77","country_code":"NL","type":"education","lineage":["https://openalex.org/I83019370"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"George Fletcher","raw_affiliation_strings":["TU Eindhoven, Eindhoven, Netherlands"],"affiliations":[{"raw_affiliation_string":"TU Eindhoven, Eindhoven, Netherlands","institution_ids":["https://openalex.org/I83019370"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082856403","display_name":"Nikolay Yakovets","orcid":"https://orcid.org/0000-0002-1488-1414"},"institutions":[{"id":"https://openalex.org/I4210091712","display_name":"Zhengzhou University of Science and Technology","ror":"https://ror.org/00b3j7936","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210091712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nikolay Yakovets","raw_affiliation_strings":["NDSC, Zhengzhou, China"],"affiliations":[{"raw_affiliation_string":"NDSC, Zhengzhou, China","institution_ids":["https://openalex.org/I4210091712"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5009692602"],"corresponding_institution_ids":["https://openalex.org/I4210091712","https://openalex.org/I83019370"],"apc_list":{"value":1190,"currency":"GBP","value_usd":1459},"apc_paid":{"value":1190,"currency":"GBP","value_usd":1459},"fwci":0.2625,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.53292092,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"10","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10742","display_name":"Peer-to-Peer Network Technologies","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10799","display_name":"Data Visualization and Analytics","score":0.9918000102043152,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/timeline","display_name":"Timeline","score":0.7942162752151489},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7040053606033325},{"id":"https://openalex.org/keywords/competition","display_name":"Competition (biology)","score":0.6137220859527588},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.6053038239479065},{"id":"https://openalex.org/keywords/cardinality","display_name":"Cardinality (data modeling)","score":0.5570698380470276},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5296611189842224},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4750090539455414},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4733871519565582},{"id":"https://openalex.org/keywords/complex-network","display_name":"Complex network","score":0.4402751326560974},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3734486401081085},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1993144154548645},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.1424354910850525}],"concepts":[{"id":"https://openalex.org/C4438859","wikidata":"https://www.wikidata.org/wiki/Q186117","display_name":"Timeline","level":2,"score":0.7942162752151489},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7040053606033325},{"id":"https://openalex.org/C91306197","wikidata":"https://www.wikidata.org/wiki/Q45767","display_name":"Competition (biology)","level":2,"score":0.6137220859527588},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.6053038239479065},{"id":"https://openalex.org/C87117476","wikidata":"https://www.wikidata.org/wiki/Q362383","display_name":"Cardinality (data modeling)","level":2,"score":0.5570698380470276},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5296611189842224},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4750090539455414},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4733871519565582},{"id":"https://openalex.org/C34947359","wikidata":"https://www.wikidata.org/wiki/Q665189","display_name":"Complex network","level":2,"score":0.4402751326560974},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3734486401081085},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1993144154548645},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.1424354910850525},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1140/epjds/s13688-021-00287-6","is_oa":true,"landing_page_url":"https://doi.org/10.1140/epjds/s13688-021-00287-6","pdf_url":"https://epjdatascience.springeropen.com/track/pdf/10.1140/epjds/s13688-021-00287-6","source":{"id":"https://openalex.org/S2504380752","display_name":"EPJ Data Science","issn_l":"2193-1127","issn":["2193-1127"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EPJ Data Science","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:ed4279c0f3ba4e939575016a9d809548","is_oa":true,"landing_page_url":"https://doaj.org/article/ed4279c0f3ba4e939575016a9d809548","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"EPJ Data Science, Vol 10, Iss 1, Pp 1-24 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1140/epjds/s13688-021-00287-6","is_oa":true,"landing_page_url":"https://doi.org/10.1140/epjds/s13688-021-00287-6","pdf_url":"https://epjdatascience.springeropen.com/track/pdf/10.1140/epjds/s13688-021-00287-6","source":{"id":"https://openalex.org/S2504380752","display_name":"EPJ Data Science","issn_l":"2193-1127","issn":["2193-1127"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EPJ Data Science","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3536022994","display_name":null,"funder_award_id":"82504","funder_id":"https://openalex.org/F4320332999","funder_display_name":"Horizon 2020 Framework Programme"},{"id":"https://openalex.org/G3791724392","display_name":null,"funder_award_id":"825041","funder_id":"https://openalex.org/F4320332999","funder_display_name":"Horizon 2020 Framework Programme"},{"id":"https://openalex.org/G7331901853","display_name":null,"funder_award_id":"EU H2020","funder_id":"https://openalex.org/F4320332999","funder_display_name":"Horizon 2020 Framework Programme"}],"funders":[{"id":"https://openalex.org/F4320332999","display_name":"Horizon 2020 Framework Programme","ror":"https://ror.org/00k4n6c32"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3167820860.pdf","grobid_xml":"https://content.openalex.org/works/W3167820860.grobid-xml"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W1553988561","https://openalex.org/W1752575990","https://openalex.org/W1966612772","https://openalex.org/W1993099985","https://openalex.org/W2042321087","https://openalex.org/W2063569667","https://openalex.org/W2064285815","https://openalex.org/W2135313865","https://openalex.org/W2146096050","https://openalex.org/W2264330624","https://openalex.org/W2474022715","https://openalex.org/W2480238113","https://openalex.org/W2516838327","https://openalex.org/W2605347441","https://openalex.org/W2615549716","https://openalex.org/W2751785830","https://openalex.org/W2962705874","https://openalex.org/W2967280136","https://openalex.org/W3098376187","https://openalex.org/W3099134950","https://openalex.org/W3100506776","https://openalex.org/W3100595176","https://openalex.org/W3106374901","https://openalex.org/W3177266595","https://openalex.org/W4412306562"],"related_works":["https://openalex.org/W1858249912","https://openalex.org/W2114034199","https://openalex.org/W2317428717","https://openalex.org/W2734259032","https://openalex.org/W4385261515","https://openalex.org/W3094038556","https://openalex.org/W4296345146","https://openalex.org/W2014772881","https://openalex.org/W2129331923","https://openalex.org/W4362637502"],"abstract_inverted_index":{"Abstract":[0],"We":[1,38,77],"study":[2],"the":[3,11,44,58,85,91],"problem":[4],"of":[5,13,19,46,55,90],"modeling":[6],"temporal":[7,20],"networks":[8,21,103,107],"constrained":[9,48],"by":[10],"size":[12],"a":[14,17,40,64,69,79],"concurrent":[15],"set,":[16],"characteristic":[18],"shown":[22],"to":[23,71,83],"be":[24],"important":[25],"in":[26,31,63,75],"many":[27],"application":[28],"areas,":[29],"e.g.,":[30],"transportation,":[32],"social,":[33],"process,":[34],"and":[35,87,105,109],"other":[36],"networks.":[37,49,93],"propose":[39],"competition-driven":[41],"model":[42,100],"for":[43],"generation":[45],"such":[47],"Our":[50,94],"method":[51],"carries":[52],"out":[53],"turns":[54],"competitions":[56],"along":[57],"timeline":[59],"where":[60],"each":[61],"node":[62],"network":[65],"is":[66],"labeled":[67],"with":[68],"probability":[70],"gain":[72],"outgoing":[73],"edges":[74],"competitions.":[76],"present":[78],"thorough":[80],"theoretical":[81],"analysis":[82],"investigate":[84],"cardinality":[86],"degree":[88],"distributions":[89],"generated":[92],"experimental":[95],"results":[96],"demonstrate":[97],"that":[98],"our":[99],"simulates":[101],"real-world":[102],"well":[104],"generates":[106],"efficiently":[108],"at":[110],"scale.":[111]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}