{"id":"https://openalex.org/W3161460925","doi":"https://doi.org/10.1145/3533725","title":"Be Causal: De-Biasing Social Network Confounding in Recommendation","display_name":"Be Causal: De-Biasing Social Network Confounding in Recommendation","publication_year":2022,"publication_date":"2022-05-05","ids":{"openalex":"https://openalex.org/W3161460925","doi":"https://doi.org/10.1145/3533725","mag":"3161460925"},"language":"en","primary_location":{"id":"doi:10.1145/3533725","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3533725","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","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/A5100340627","display_name":"Qian Li","orcid":"https://orcid.org/0000-0002-8308-9551"},"institutions":[{"id":"https://openalex.org/I205640436","display_name":"Curtin University","ror":"https://ror.org/02n415q13","country_code":"AU","type":"education","lineage":["https://openalex.org/I205640436"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Qian Li","raw_affiliation_strings":["School of Electrical Engineering Computing and Mathematical Sciences, Curtin University, Perth, WA, Australia"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering Computing and Mathematical Sciences, Curtin University, Perth, WA, Australia","institution_ids":["https://openalex.org/I205640436"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010481978","display_name":"Xiangmeng Wang","orcid":"https://orcid.org/0000-0003-3643-3353"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Xiangmeng Wang","raw_affiliation_strings":["Data Science and Machine Intelligence Lab, University of Technology Sydney, Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"Data Science and Machine Intelligence Lab, University of Technology Sydney, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051604406","display_name":"Zhichao Wang","orcid":"https://orcid.org/0000-0003-1326-0859"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Zhichao Wang","raw_affiliation_strings":["University of New South Wales, Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"University of New South Wales, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051512158","display_name":"Guandong Xu","orcid":"https://orcid.org/0000-0003-4493-6663"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Guandong Xu","raw_affiliation_strings":["Data Science and Machine Intelligence Lab, University of Technology Sydney, Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"Data Science and Machine Intelligence Lab, University of Technology Sydney, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I114017466"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100340627"],"corresponding_institution_ids":["https://openalex.org/I205640436"],"apc_list":null,"apc_paid":null,"fwci":17.8205,"has_fulltext":false,"cited_by_count":60,"citation_normalized_percentile":{"value":0.99234582,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"17","issue":"1","first_page":"1","last_page":"23"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9930999875068665,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9850000143051147,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/causal-inference","display_name":"Causal inference","score":0.6529721617698669},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.61161869764328},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.6056509613990784},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.5887263417243958},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5861418843269348},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.5771432518959045},{"id":"https://openalex.org/keywords/confounding","display_name":"Confounding","score":0.5755036473274231},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46624699234962463},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.46536970138549805},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4381732940673828},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3512980341911316},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.3001815378665924},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.23951539397239685},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1808050572872162}],"concepts":[{"id":"https://openalex.org/C158600405","wikidata":"https://www.wikidata.org/wiki/Q5054566","display_name":"Causal inference","level":2,"score":0.6529721617698669},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.61161869764328},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.6056509613990784},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.5887263417243958},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5861418843269348},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.5771432518959045},{"id":"https://openalex.org/C77350462","wikidata":"https://www.wikidata.org/wiki/Q1125472","display_name":"Confounding","level":2,"score":0.5755036473274231},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46624699234962463},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.46536970138549805},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4381732940673828},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3512980341911316},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3001815378665924},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.23951539397239685},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1808050572872162},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3533725","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3533725","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.699999988079071,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G7414605540","display_name":null,"funder_award_id":"DP220103717, LE220100078, LP170100891, and DP200101374","funder_id":"https://openalex.org/F4320334704","funder_display_name":"Australian Research Council"}],"funders":[{"id":"https://openalex.org/F4320334704","display_name":"Australian Research Council","ror":"https://ror.org/05mmh0f86"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":66,"referenced_works":["https://openalex.org/W114517082","https://openalex.org/W1533861849","https://openalex.org/W1886704267","https://openalex.org/W1888005072","https://openalex.org/W1990846291","https://openalex.org/W1992665562","https://openalex.org/W1994389483","https://openalex.org/W2009205701","https://openalex.org/W2013170277","https://openalex.org/W2020631728","https://openalex.org/W2026773017","https://openalex.org/W2045745608","https://openalex.org/W2046974451","https://openalex.org/W2057685268","https://openalex.org/W2080320419","https://openalex.org/W2100358124","https://openalex.org/W2101409192","https://openalex.org/W2122124659","https://openalex.org/W2124187902","https://openalex.org/W2132917208","https://openalex.org/W2135598826","https://openalex.org/W2137245235","https://openalex.org/W2144487656","https://openalex.org/W2157519573","https://openalex.org/W2188353343","https://openalex.org/W2313407065","https://openalex.org/W2328111639","https://openalex.org/W2340502990","https://openalex.org/W2393319904","https://openalex.org/W2509678028","https://openalex.org/W2531563875","https://openalex.org/W2604662567","https://openalex.org/W2604738573","https://openalex.org/W2629213068","https://openalex.org/W2736141399","https://openalex.org/W2739992143","https://openalex.org/W2886453691","https://openalex.org/W2892888989","https://openalex.org/W2899656399","https://openalex.org/W2907727731","https://openalex.org/W2908074993","https://openalex.org/W2910376060","https://openalex.org/W2914721378","https://openalex.org/W2945684222","https://openalex.org/W2949976336","https://openalex.org/W2952613481","https://openalex.org/W2962695761","https://openalex.org/W2962756421","https://openalex.org/W2962975498","https://openalex.org/W2998534896","https://openalex.org/W3020940496","https://openalex.org/W3034348890","https://openalex.org/W3035404611","https://openalex.org/W3040526978","https://openalex.org/W3103310105","https://openalex.org/W3105705953","https://openalex.org/W3124244238","https://openalex.org/W3205333154","https://openalex.org/W3210379211","https://openalex.org/W4212874084","https://openalex.org/W4224313551","https://openalex.org/W4256306241","https://openalex.org/W4289029551","https://openalex.org/W4299828299","https://openalex.org/W6684173853","https://openalex.org/W6807988415"],"related_works":["https://openalex.org/W3023719900","https://openalex.org/W4287798354","https://openalex.org/W3035083705","https://openalex.org/W2030287811","https://openalex.org/W3002087755","https://openalex.org/W4386534229","https://openalex.org/W4386150491","https://openalex.org/W2806152055","https://openalex.org/W4301105698","https://openalex.org/W4286896224"],"abstract_inverted_index":{"In":[0,111],"recommendation":[1,18],"systems,":[2],"the":[3,6,12,17,33,50,64,76,86,122,136,144,150,161,167,179,193],"existence":[4],"of":[5,49],"missing-not-at-random":[7],"(MNAR)":[8],"problem":[9],"results":[10],"in":[11,101,108,140],"selection":[13],"bias":[14],"issue,":[15],"degrading":[16],"performance":[19],"ultimately.":[20],"A":[21],"common":[22],"practice":[23],"to":[24,28,45,62,73,165],"address":[25],"MNAR":[26,119],"is":[27,42],"treat":[29],"missing":[30,79],"entries":[31],"from":[32,80,120],"so-called":[34],"\u201cexposure\u201d":[35],"perspective,":[36],"i.e.,":[37],"modeling":[38],"how":[39,75],"an":[40,90],"item":[41,129,171],"exposed":[43],"(provided)":[44],"a":[46,81,115,157],"user.":[47],"Most":[48],"existing":[51],"approaches":[52],"use":[53],"heuristic":[54],"models":[55],"or":[56,128],"re-weighting":[57],"strategy":[58],"on":[59,118,178,184],"observed":[60,151],"ratings":[61,77],"mimic":[63],"missing-at-random":[65],"setting.":[66],"However,":[67],"little":[68],"research":[69],"has":[70],"been":[71],"done":[72],"reveal":[74],"are":[78],"causal":[82,109,116],"perspective.":[83,134],"To":[84],"bridge":[85],"gap,":[87],"we":[88],"propose":[89],"unbiased":[91],"and":[92,131,170],"robust":[93],"method":[94],"called":[95],"DENC":[96,113,141,175],"(":[97],"De-Bias":[98],"Network":[99],"Confounding":[100],"Recommendation":[102],"),":[103],"inspired":[104],"by":[105],"confounder":[106,147],"analysis":[107,117],"inference.":[110],"general,":[112],"provides":[114],"both":[121],"inherent":[123],"factors":[124],"(e.g.,":[125],"latent":[126],"user":[127,169],"factors)":[130],"auxiliary":[132],"network\u2019s":[133],"Particularly,":[135],"proposed":[137,190],"exposure":[138,152],"model":[139,159,191],"can":[142],"control":[143],"social":[145],"network":[146],"meanwhile":[148],"preserve":[149],"information.":[153],"We":[154],"also":[155],"develop":[156],"deconfounding":[158],"through":[160],"balanced":[162],"representation":[163],"learning":[164],"retain":[166],"primary":[168],"features,":[172],"which":[173],"enables":[174],"generalize":[176],"well":[177],"rating":[180],"prediction.":[181],"Extensive":[182],"experiments":[183],"three":[185],"datasets":[186],"validate":[187],"that":[188],"our":[189],"outperforms":[192],"state-of-the-art":[194],"baselines.":[195]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":21},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-18T14:38:29.013473","created_date":"2025-10-10T00:00:00"}