{"id":"https://openalex.org/W3023651562","doi":"https://doi.org/10.1145/3366424.3383301","title":"Dynamic Network Modeling from Motif-Activity","display_name":"Dynamic Network Modeling from Motif-Activity","publication_year":2020,"publication_date":"2020-04-20","ids":{"openalex":"https://openalex.org/W3023651562","doi":"https://doi.org/10.1145/3366424.3383301","mag":"3023651562"},"language":"en","primary_location":{"id":"doi:10.1145/3366424.3383301","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3366424.3383301","pdf_url":null,"source":{"id":"https://openalex.org/S4306506651","display_name":"Companion Proceedings of the Web Conference 2020","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of the Web Conference 2020","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1145/3366424.3383301","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5012683483","display_name":"Giselle Zeno","orcid":"https://orcid.org/0009-0009-5011-7163"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Giselle Zeno","raw_affiliation_strings":["Purdue University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Purdue University","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084693605","display_name":"Timothy La Fond","orcid":null},"institutions":[{"id":"https://openalex.org/I1282311441","display_name":"Lawrence Livermore National Laboratory","ror":"https://ror.org/041nk4h53","country_code":"US","type":"facility","lineage":["https://openalex.org/I1282311441","https://openalex.org/I1330989302","https://openalex.org/I198811213","https://openalex.org/I4210138311"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Timothy La Fond","raw_affiliation_strings":["Lawrence Livermore National Laboratory"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Lawrence Livermore National Laboratory","institution_ids":["https://openalex.org/I1282311441"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064439579","display_name":"Jennifer Neville","orcid":"https://orcid.org/0000-0001-8108-4899"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jennifer Neville","raw_affiliation_strings":["Purdue University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Purdue University","institution_ids":["https://openalex.org/I219193219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3021,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.7924665,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"390","last_page":"397"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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/T10799","display_name":"Data Visualization and Analytics","score":0.9948999881744385,"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"}},{"id":"https://openalex.org/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.979200005531311,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.726451575756073},{"id":"https://openalex.org/keywords/motif","display_name":"Motif (music)","score":0.6063124537467957},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5772494077682495},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.5304533839225769},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.47750037908554077},{"id":"https://openalex.org/keywords/dynamic-network-analysis","display_name":"Dynamic network analysis","score":0.47371548414230347},{"id":"https://openalex.org/keywords/network-motif","display_name":"Network motif","score":0.469635933637619},{"id":"https://openalex.org/keywords/structural-motif","display_name":"Structural motif","score":0.43483343720436096},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.3595341145992279},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33993738889694214},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33688730001449585},{"id":"https://openalex.org/keywords/complex-network","display_name":"Complex network","score":0.3204301595687866}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.726451575756073},{"id":"https://openalex.org/C32276052","wikidata":"https://www.wikidata.org/wiki/Q908349","display_name":"Motif (music)","level":2,"score":0.6063124537467957},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5772494077682495},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5304533839225769},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.47750037908554077},{"id":"https://openalex.org/C13540734","wikidata":"https://www.wikidata.org/wiki/Q5318996","display_name":"Dynamic network analysis","level":2,"score":0.47371548414230347},{"id":"https://openalex.org/C60723933","wikidata":"https://www.wikidata.org/wiki/Q7001080","display_name":"Network motif","level":3,"score":0.469635933637619},{"id":"https://openalex.org/C132677234","wikidata":"https://www.wikidata.org/wiki/Q3273544","display_name":"Structural motif","level":2,"score":0.43483343720436096},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.3595341145992279},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33993738889694214},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33688730001449585},{"id":"https://openalex.org/C34947359","wikidata":"https://www.wikidata.org/wiki/Q665189","display_name":"Complex network","level":2,"score":0.3204301595687866},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C46141821","wikidata":"https://www.wikidata.org/wiki/Q209402","display_name":"Nuclear magnetic resonance","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3366424.3383301","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3366424.3383301","pdf_url":null,"source":{"id":"https://openalex.org/S4306506651","display_name":"Companion Proceedings of the Web Conference 2020","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of the Web Conference 2020","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3366424.3383301","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3366424.3383301","pdf_url":null,"source":{"id":"https://openalex.org/S4306506651","display_name":"Companion Proceedings of the Web Conference 2020","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of the Web Conference 2020","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W131619556","https://openalex.org/W753235638","https://openalex.org/W1603920809","https://openalex.org/W1900217900","https://openalex.org/W1937334562","https://openalex.org/W1987236914","https://openalex.org/W1993099985","https://openalex.org/W2027377866","https://openalex.org/W2033219385","https://openalex.org/W2053998171","https://openalex.org/W2060630617","https://openalex.org/W2076844992","https://openalex.org/W2080427922","https://openalex.org/W2086639361","https://openalex.org/W2108614537","https://openalex.org/W2123098252","https://openalex.org/W2135303340","https://openalex.org/W2144799688","https://openalex.org/W2146096050","https://openalex.org/W2153624566","https://openalex.org/W2157463825","https://openalex.org/W2210136478","https://openalex.org/W2264330624","https://openalex.org/W2562676961","https://openalex.org/W2785658572","https://openalex.org/W2787887656","https://openalex.org/W2792749098","https://openalex.org/W2952695746","https://openalex.org/W3004555699","https://openalex.org/W3100506776","https://openalex.org/W3101251439","https://openalex.org/W3102446989","https://openalex.org/W4312512934"],"related_works":["https://openalex.org/W3079957389","https://openalex.org/W4205962317","https://openalex.org/W2368410102","https://openalex.org/W3113308218","https://openalex.org/W3021477453","https://openalex.org/W2364249514","https://openalex.org/W2938754949","https://openalex.org/W2610941444","https://openalex.org/W2132757463","https://openalex.org/W4288366168"],"abstract_inverted_index":{"Graph":[0],"structure":[1,29,44,128,153],"in":[2,54,82,130,163],"dynamic":[3,15,56,103,119,164],"networks":[4,16],"changes":[5,30,161],"rapidly.":[6],"Using":[7],"temporal":[8],"information":[9],"about":[10],"their":[11,28,91,156],"connections,":[12],"models":[13],"for":[14,42,100],"can":[17],"be":[18],"developed":[19],"and":[20,77,86,135,154],"used":[21,140],"to":[22,71],"understand":[23],"the":[24,43,87,95,131,138,150,159],"process":[25],"of":[26,45],"how":[27],"over":[31],"time.":[32],"Additionally,":[33],"higher-order":[34],"motifs":[35,60,80,148],"have":[36],"been":[37],"established":[38],"as":[39,141],"building":[40],"blocks":[41],"networks.":[46,165],"In":[47],"this":[48],"paper,":[49],"we":[50],"first":[51],"demonstrate":[52],"empirically":[53],"three":[55],"network":[57],"datasets,":[58],"that":[59,146],"with":[61,105,117,137],"edges:":[62],"(1)":[63],"do":[64],"not":[65],"transition":[66],"from":[67,108],"one":[68],"motif":[69],"type":[70],"another":[72],"(e.g,":[73],"wedges":[74],"becoming":[75],"triangles":[76],"vice-versa);":[78],"(2)":[79],"re-appear":[81],"other":[83],"time":[84],"periods":[85],"rate":[88],"depends":[89],"on":[90],"configuration.":[92],"We":[93,112],"propose":[94],"Dynamic":[96],"Motif-Activity":[97],"Model":[98],"(DMA)":[99],"sampling":[101],"synthetic":[102,133],"graphs":[104,134],"parameters":[106],"learned":[107],"an":[109],"observed":[110],"network.":[111],"evaluate":[113],"our":[114],"DMA":[115],"model,":[116],"two":[118],"graph":[120,127,139,152],"generative":[121],"model":[122],"baselines,":[123],"by":[124],"measuring":[125],"different":[126],"metrics":[129],"generated":[132],"comparing":[136],"input.":[142],"Our":[143],"results":[144],"show":[145],"employing":[147],"captures":[149],"underlying":[151],"modeling":[155],"activity":[157],"recreates":[158],"fast":[160],"seen":[162]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
