{"id":"https://openalex.org/W4385565201","doi":"https://doi.org/10.1145/3580305.3599555","title":"Fairness in Graph Machine Learning: Recent Advances and Future Prospectives","display_name":"Fairness in Graph Machine Learning: Recent Advances and Future Prospectives","publication_year":2023,"publication_date":"2023-08-04","ids":{"openalex":"https://openalex.org/W4385565201","doi":"https://doi.org/10.1145/3580305.3599555"},"language":"en","primary_location":{"id":"doi:10.1145/3580305.3599555","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3580305.3599555","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-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/A5047581320","display_name":"Yushun Dong","orcid":"https://orcid.org/0000-0001-7504-6159"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yushun Dong","raw_affiliation_strings":["University of Virginia, Charlottesville, USA"],"affiliations":[{"raw_affiliation_string":"University of Virginia, Charlottesville, USA","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015639730","display_name":"\u00d6yk\u00fc Deniz K\u00f6se","orcid":"https://orcid.org/0000-0002-8685-2161"},"institutions":[{"id":"https://openalex.org/I204250578","display_name":"University of California, Irvine","ror":"https://ror.org/04gyf1771","country_code":"US","type":"education","lineage":["https://openalex.org/I204250578"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Oyku Deniz Kose","raw_affiliation_strings":["University of California, Irvine, Irvine, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of California, Irvine, Irvine, CA, USA","institution_ids":["https://openalex.org/I204250578"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019337064","display_name":"Yanning Shen","orcid":"https://orcid.org/0000-0002-7333-893X"},"institutions":[{"id":"https://openalex.org/I204250578","display_name":"University of California, Irvine","ror":"https://ror.org/04gyf1771","country_code":"US","type":"education","lineage":["https://openalex.org/I204250578"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yanning Shen","raw_affiliation_strings":["University of California, Irvine, Irvine, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of California, Irvine, Irvine, CA, USA","institution_ids":["https://openalex.org/I204250578"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029588473","display_name":"Jundong Li","orcid":"https://orcid.org/0000-0002-1878-817X"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jundong Li","raw_affiliation_strings":["University of Virginia, Charlottesville, USA"],"affiliations":[{"raw_affiliation_string":"University of Virginia, Charlottesville, USA","institution_ids":["https://openalex.org/I51556381"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5047581320"],"corresponding_institution_ids":["https://openalex.org/I51556381"],"apc_list":null,"apc_paid":null,"fwci":1.0345,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.80898114,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"5794","last_page":"5795"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10883","display_name":"Ethics and Social Impacts of AI","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10883","display_name":"Ethics and Social Impacts of AI","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9782999753952026,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9574000239372253,"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":0.7669297456741333},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.7600058913230896},{"id":"https://openalex.org/keywords/debiasing","display_name":"Debiasing","score":0.6991338729858398},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6346156001091003},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5569891333580017},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3755740821361542},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.36570531129837036},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3464149832725525},{"id":"https://openalex.org/keywords/cognitive-science","display_name":"Cognitive science","score":0.07507947087287903}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7669297456741333},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7600058913230896},{"id":"https://openalex.org/C2779458634","wikidata":"https://www.wikidata.org/wiki/Q24963715","display_name":"Debiasing","level":2,"score":0.6991338729858398},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6346156001091003},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5569891333580017},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3755740821361542},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.36570531129837036},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3464149832725525},{"id":"https://openalex.org/C188147891","wikidata":"https://www.wikidata.org/wiki/Q147638","display_name":"Cognitive science","level":1,"score":0.07507947087287903},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3580305.3599555","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3580305.3599555","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7099999785423279,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W2100960835","https://openalex.org/W3022163979","https://openalex.org/W3171764584","https://openalex.org/W4224923629","https://openalex.org/W4281861579","https://openalex.org/W4283661164","https://openalex.org/W4312668266","https://openalex.org/W4365393360","https://openalex.org/W4382239201","https://openalex.org/W6604424379"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4224009465","https://openalex.org/W4286629047","https://openalex.org/W4306321456","https://openalex.org/W4285260836","https://openalex.org/W3046775127","https://openalex.org/W3170094116","https://openalex.org/W4205958290","https://openalex.org/W4386462264"],"abstract_inverted_index":{"Graph":[0],"machine":[1,25,70,92,124,137,151],"learning":[2,26,71,93,125,138,152],"algorithms":[3,27,94,153],"have":[4],"become":[5],"popular":[6],"tools":[7],"in":[8,35,58,68,85,91,122],"helping":[9],"us":[10],"gain":[11],"a":[12,45,49,78,113,129],"deeper":[13],"understanding":[14,119],"of":[15,65,81,116,120,131],"the":[16,55,63,89,107,117],"ubiquitous":[17],"graph":[18,24,69,123,136,150],"data.":[19],"Despite":[20],"their":[21],"effectiveness,":[22],"most":[23],"lack":[28],"considerations":[29],"for":[30],"fairness,":[31],"which":[32],"can":[33],"result":[34],"discriminatory":[36],"outcomes":[37],"against":[38],"certain":[39],"demographic":[40],"subgroups":[41],"or":[42],"individuals.":[43],"As":[44],"result,":[46],"there":[47],"is":[48],"growing":[50],"societal":[51],"concern":[52],"about":[53],"mitigating":[54,88],"bias":[56,67,90,121],"exhibited":[57],"these":[59,149],"algorithms.":[60,139],"To":[61],"tackle":[62],"problem":[64],"algorithmic":[66],"algorithms,":[72,126],"this":[73,98],"tutorial":[74,99],"aims":[75],"to":[76,134,167],"provide":[77,158],"comprehensive":[79],"overview":[80],"recent":[82],"research":[83,162],"progress":[84],"measuring":[86],"and":[87,106,164],"on":[95,160],"graphs.":[96],"Specifically,":[97],"first":[100],"introduces":[101],"several":[102],"widely-used":[103],"fairness":[104],"notions":[105],"corresponding":[108],"metrics.":[109],"Then,":[110],"we":[111,141,157],"present":[112],"well-organized":[114],"review":[115],"theoretical":[118],"followed":[127],"by":[128],"summary":[130],"existing":[132],"techniques":[133],"debias":[135],"Furthermore,":[140],"demonstrate":[142],"how":[143],"different":[144],"real-world":[145],"applications":[146],"benefit":[147],"from":[148],"after":[154],"debiasing.":[155],"Finally,":[156],"insights":[159],"current":[161],"challenges":[163],"open":[165],"questions":[166],"encourage":[168],"further":[169],"advances.":[170]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}