{"id":"https://openalex.org/W3128577619","doi":"https://doi.org/10.1109/tkde.2021.3056884","title":"Auditing Network Embedding: An Edge Influence Based Approach","display_name":"Auditing Network Embedding: An Edge Influence Based Approach","publication_year":2021,"publication_date":"2021-02-07","ids":{"openalex":"https://openalex.org/W3128577619","doi":"https://doi.org/10.1109/tkde.2021.3056884","mag":"3128577619"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2021.3056884","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2021.3056884","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101456921","display_name":"Yaojing Wang","orcid":"https://orcid.org/0000-0002-8863-0829"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaojing Wang","raw_affiliation_strings":["State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, Jiangsu, China"],"raw_orcid":"https://orcid.org/0000-0002-8863-0829","affiliations":[{"raw_affiliation_string":"State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, Jiangsu, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068643894","display_name":"Yuan Yao","orcid":"https://orcid.org/0000-0002-6913-6542"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Yao","raw_affiliation_strings":["State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, Jiangsu, China"],"raw_orcid":"https://orcid.org/0000-0002-6913-6542","affiliations":[{"raw_affiliation_string":"State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, Jiangsu, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068043486","display_name":"Hanghang Tong","orcid":"https://orcid.org/0000-0003-4405-3887"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hanghang Tong","raw_affiliation_strings":["University of Illinois at Urbana-Champaign, Champaign, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Illinois at Urbana-Champaign, Champaign, IL, USA","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112579705","display_name":"Feng Xu","orcid":"https://orcid.org/0000-0003-3347-7510"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Xu","raw_affiliation_strings":["State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, Jiangsu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, Jiangsu, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037645622","display_name":"Jian L\u00fc","orcid":"https://orcid.org/0000-0002-7025-7448"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Lu","raw_affiliation_strings":["State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, Jiangsu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, Jiangsu, China","institution_ids":["https://openalex.org/I881766915"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4198,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.67619939,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"34","issue":"11","first_page":"5211","last_page":"5224"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9894999861717224,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9088000059127808,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/computer-science","display_name":"Computer science","score":0.7626625299453735},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.7311781644821167},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.6310660243034363},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.6060424447059631},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5464961528778076},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.537532389163971},{"id":"https://openalex.org/keywords/notation","display_name":"Notation","score":0.46651020646095276},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37688469886779785},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35437482595443726},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32440030574798584},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15795478224754333}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7626625299453735},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.7311781644821167},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.6310660243034363},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.6060424447059631},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5464961528778076},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.537532389163971},{"id":"https://openalex.org/C45357846","wikidata":"https://www.wikidata.org/wiki/Q2001982","display_name":"Notation","level":2,"score":0.46651020646095276},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37688469886779785},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35437482595443726},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32440030574798584},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15795478224754333},{"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/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2021.3056884","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2021.3056884","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1888249465","display_name":"\u81ea\u6210\u957f\u590d\u6742\u8f6f\u4ef6\u7cfb\u7edf\u6784\u5efa\u65b9\u6cd5\u4e0e\u8fd0\u884c\u652f\u6491\u7814\u7a76","funder_award_id":"61932021","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":107,"referenced_works":["https://openalex.org/W1614298861","https://openalex.org/W1662382123","https://openalex.org/W1888005072","https://openalex.org/W2006903949","https://openalex.org/W2062075162","https://openalex.org/W2062797058","https://openalex.org/W2090891622","https://openalex.org/W2145658888","https://openalex.org/W2154851992","https://openalex.org/W2242161203","https://openalex.org/W2271982975","https://openalex.org/W2294347342","https://openalex.org/W2387462954","https://openalex.org/W2393319904","https://openalex.org/W2415243320","https://openalex.org/W2510508396","https://openalex.org/W2536880093","https://openalex.org/W2574817444","https://openalex.org/W2583803680","https://openalex.org/W2584620251","https://openalex.org/W2597603852","https://openalex.org/W2604942799","https://openalex.org/W2605234117","https://openalex.org/W2607500032","https://openalex.org/W2623187518","https://openalex.org/W2743104969","https://openalex.org/W2767460050","https://openalex.org/W2767500585","https://openalex.org/W2767774008","https://openalex.org/W2787927827","https://openalex.org/W2788045146","https://openalex.org/W2788284887","https://openalex.org/W2788338934","https://openalex.org/W2788379054","https://openalex.org/W2788614083","https://openalex.org/W2797744353","https://openalex.org/W2803831897","https://openalex.org/W2808000122","https://openalex.org/W2808771744","https://openalex.org/W2808908091","https://openalex.org/W2808923352","https://openalex.org/W2808987817","https://openalex.org/W2809219720","https://openalex.org/W2809418595","https://openalex.org/W2809435521","https://openalex.org/W2896808365","https://openalex.org/W2901375380","https://openalex.org/W2914833637","https://openalex.org/W2914999862","https://openalex.org/W2916106175","https://openalex.org/W2945827377","https://openalex.org/W2946297661","https://openalex.org/W2950723285","https://openalex.org/W2952344766","https://openalex.org/W2962756421","https://openalex.org/W2962904108","https://openalex.org/W2962975498","https://openalex.org/W2963017945","https://openalex.org/W2963169753","https://openalex.org/W2963224980","https://openalex.org/W2963312446","https://openalex.org/W2963603080","https://openalex.org/W2963695795","https://openalex.org/W2964015378","https://openalex.org/W2964113829","https://openalex.org/W2964145825","https://openalex.org/W2964283260","https://openalex.org/W2964321699","https://openalex.org/W2983269435","https://openalex.org/W3005644236","https://openalex.org/W3023001449","https://openalex.org/W3094040844","https://openalex.org/W3098276446","https://openalex.org/W3098702884","https://openalex.org/W3101553402","https://openalex.org/W3102205844","https://openalex.org/W3103254545","https://openalex.org/W3103311102","https://openalex.org/W3104097132","https://openalex.org/W4244387885","https://openalex.org/W4251194840","https://openalex.org/W4291474301","https://openalex.org/W4293651439","https://openalex.org/W4294170691","https://openalex.org/W4294558607","https://openalex.org/W4297733535","https://openalex.org/W4322614756","https://openalex.org/W6636510571","https://openalex.org/W6637178625","https://openalex.org/W6682691769","https://openalex.org/W6685350579","https://openalex.org/W6690230747","https://openalex.org/W6693836888","https://openalex.org/W6699364125","https://openalex.org/W6713582119","https://openalex.org/W6720006811","https://openalex.org/W6730084236","https://openalex.org/W6731976766","https://openalex.org/W6735632633","https://openalex.org/W6738964360","https://openalex.org/W6744557953","https://openalex.org/W6748799445","https://openalex.org/W6751569023","https://openalex.org/W6754578491","https://openalex.org/W6760001035","https://openalex.org/W6762814303","https://openalex.org/W6771621015"],"related_works":["https://openalex.org/W2963177394","https://openalex.org/W2024638892","https://openalex.org/W763418848","https://openalex.org/W1595229445","https://openalex.org/W1965815883","https://openalex.org/W149041114","https://openalex.org/W4313359513","https://openalex.org/W322408318","https://openalex.org/W4298135613","https://openalex.org/W2932872266"],"abstract_inverted_index":{"Learning":[0],"node":[1,25,63,69,116],"representations":[2,26,64,70],"in":[3,143,169,186],"a":[4,7,56,183],"network":[5,30,51,93,131],"has":[6],"wide":[8],"range":[9],"of":[10,13,22,45,75,92,145,171,189],"applications.":[11],"Most":[12],"the":[14,20,23,46,49,61,67,73,76,85,112,125,149,175,179,187],"existing":[15,50],"work":[16],"focuses":[17],"on":[18,115,137],"improving":[19],"performance":[21],"learned":[24],"by":[27,123,178],"designing":[28],"advanced":[29],"embedding":[31,52,58,94],"models.":[32],"In":[33,79],"contrast":[34],"to":[35,41,72,83,107,156],"these":[36],"work,":[37],"this":[38],"article":[39],"aims":[40],"provide":[42,105],"some":[43],"understanding":[44],"rationale":[47],"behind":[48],"models,":[53,95],"e.g.,":[54],"<i>why</i>":[55],"given":[57],"algorithm":[59],"outputs":[60],"specific":[62],"and":[65,100,109,118,130,167,193],"<i>how</i>":[66],"resulting":[68],"relate":[71],"structure":[74],"input":[77],"network.":[78],"particular,":[80],"we":[81],"propose":[82],"discern":[84],"edge":[86,113,128,147],"influence":[87,114,129],"for":[88],"two":[89],"widely-studied":[90],"classes":[91],"i.e.,":[96],"skip-gram":[97],"based":[98],"models":[99],"graph":[101],"neural":[102],"networks.":[103],"We":[104],"algorithms":[106],"effectively":[108],"efficiently":[110],"quantify":[111],"representations,":[117],"further":[119],"identify":[120],"high-influential":[121,173],"edges":[122,177],"exploiting":[124],"linkage":[126],"between":[127],"structure.":[132],"Experimental":[133],"evaluations":[134],"are":[135],"conducted":[136],"real":[138],"datasets":[139],"showing":[140],"that:":[141],"1)":[142],"terms":[144,170],"quantifying":[146],"influence,":[148],"proposed":[150,180],"method":[151,181],"is":[152],"significantly":[153],"faster":[154],"(up":[155],"<inline-formula><tex-math":[157],"notation=\"LaTeX\">$2,000\\times$</tex-math></inline-formula>":[158],")":[159],"than":[160],"straightforward":[161],"methods":[162],"with":[163],"little":[164],"quality":[165],"loss,":[166],"2)":[168],"identifying":[172],"edges,":[174],"identified":[176],"have":[182],"significant":[184],"impact":[185],"context":[188],"downstream":[190],"prediction":[191],"task":[192],"adversarial":[194],"attacking.":[195]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}