{"id":"https://openalex.org/W4212977715","doi":"https://doi.org/10.1145/3488560.3498468","title":"A Counterfactual Modeling Framework for Churn Prediction","display_name":"A Counterfactual Modeling Framework for Churn Prediction","publication_year":2022,"publication_date":"2022-02-11","ids":{"openalex":"https://openalex.org/W4212977715","doi":"https://doi.org/10.1145/3488560.3498468"},"language":"en","primary_location":{"id":"doi:10.1145/3488560.3498468","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3488560.3498468","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3488560.3498468","source":{"id":"https://openalex.org/S4363608885","display_name":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3488560.3498468","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100711272","display_name":"Guozhen Zhang","orcid":"https://orcid.org/0000-0003-0125-9666"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Guozhen Zhang","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055452361","display_name":"Jinwei Zeng","orcid":"https://orcid.org/0000-0003-4481-413X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinwei Zeng","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081760084","display_name":"Zhengyue Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhengyue Zhao","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044100655","display_name":"Depeng Jin","orcid":"https://orcid.org/0000-0003-0419-5514"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Depeng Jin","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100355277","display_name":"Yong Li","orcid":"https://orcid.org/0000-0001-5617-1659"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Li","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100711272"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":2.1891,"has_fulltext":true,"cited_by_count":17,"citation_normalized_percentile":{"value":0.8950829,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1424","last_page":"1432"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9993000030517578,"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":0.9993000030517578,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9940000176429749,"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/T12384","display_name":"Customer churn and segmentation","score":0.9936000108718872,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/counterfactual-thinking","display_name":"Counterfactual thinking","score":0.9773499965667725},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7837064862251282},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.5840737819671631},{"id":"https://openalex.org/keywords/causal-model","display_name":"Causal model","score":0.5733058452606201},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5208749771118164},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4985466003417969},{"id":"https://openalex.org/keywords/causal-analysis","display_name":"Causal analysis","score":0.41164225339889526},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4005906581878662},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.34694159030914307},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.31730666756629944},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0829765796661377}],"concepts":[{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.9773499965667725},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7837064862251282},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.5840737819671631},{"id":"https://openalex.org/C11671645","wikidata":"https://www.wikidata.org/wiki/Q5054567","display_name":"Causal model","level":2,"score":0.5733058452606201},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5208749771118164},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4985466003417969},{"id":"https://openalex.org/C2987525970","wikidata":"https://www.wikidata.org/wiki/Q96374569","display_name":"Causal analysis","level":2,"score":0.41164225339889526},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4005906581878662},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.34694159030914307},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.31730666756629944},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0829765796661377},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3488560.3498468","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3488560.3498468","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3488560.3498468","source":{"id":"https://openalex.org/S4363608885","display_name":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3488560.3498468","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3488560.3498468","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3488560.3498468","source":{"id":"https://openalex.org/S4363608885","display_name":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1121271761","display_name":null,"funder_award_id":"Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1757078732","display_name":null,"funder_award_id":"20031887521","funder_id":"https://openalex.org/F4320329777","funder_display_name":"Beijing National Research Center For Information Science And Technology"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2236719086","display_name":null,"funder_award_id":"L182038","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2347204971","display_name":null,"funder_award_id":"20031887521","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G2792346265","display_name":null,"funder_award_id":"2018YFB1800804","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3710896277","display_name":null,"funder_award_id":"61971267","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3734416573","display_name":null,"funder_award_id":"61972223","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G391238517","display_name":null,"funder_award_id":", and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4542831392","display_name":null,"funder_award_id":"61861136003","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4835573105","display_name":null,"funder_award_id":"2018YFB1800804","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4872662616","display_name":null,"funder_award_id":"U1936217","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5268169751","display_name":null,"funder_award_id":"61941117","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5939423041","display_name":null,"funder_award_id":"Technology","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6867336257","display_name":null,"funder_award_id":"U1936217, 61971267, 61972223","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G832729633","display_name":null,"funder_award_id":"61136003","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8724681935","display_name":null,"funder_award_id":"U1936217, 61971267, 61972223, 61941117, 61861136003","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320316083","display_name":"Tencent","ror":"https://ror.org/00hhjss72"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322392","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549"},{"id":"https://openalex.org/F4320329777","display_name":"Beijing National Research Center For Information Science And Technology","ror":null},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4212977715.pdf","grobid_xml":"https://content.openalex.org/works/W4212977715.grobid-xml"},"referenced_works_count":29,"referenced_works":["https://openalex.org/W1490576214","https://openalex.org/W1994599624","https://openalex.org/W2048531216","https://openalex.org/W2053193751","https://openalex.org/W2053768216","https://openalex.org/W2087088589","https://openalex.org/W2096365673","https://openalex.org/W2132917208","https://openalex.org/W2150291618","https://openalex.org/W2167312400","https://openalex.org/W2187089797","https://openalex.org/W2618036913","https://openalex.org/W2629213068","https://openalex.org/W2795034086","https://openalex.org/W2809496930","https://openalex.org/W2809583854","https://openalex.org/W2914721378","https://openalex.org/W2939289155","https://openalex.org/W2950164091","https://openalex.org/W2972659741","https://openalex.org/W3002293096","https://openalex.org/W3031101592","https://openalex.org/W3044963235","https://openalex.org/W3100875635","https://openalex.org/W3103310105","https://openalex.org/W3104249938","https://openalex.org/W3104589861","https://openalex.org/W3156961168","https://openalex.org/W4288107043"],"related_works":["https://openalex.org/W1498469922","https://openalex.org/W4243804444","https://openalex.org/W4372260129","https://openalex.org/W3088104152","https://openalex.org/W4280530714","https://openalex.org/W1968819517","https://openalex.org/W1988627926","https://openalex.org/W4313422683","https://openalex.org/W4251313373","https://openalex.org/W4403292511"],"abstract_inverted_index":{"Accurate":[0],"churn":[1,47,74,113,129,147,194,244],"prediction":[2,51,182,212,227],"for":[3,9,33,112,125],"retaining":[4],"users":[5],"is":[6,75,85],"keenly":[7],"important":[8,31],"online":[10],"services":[11],"because":[12],"it":[13],"determines":[14],"their":[15],"survival":[16],"and":[17,36,95,127,149,241],"prosperity.":[18],"Recent":[19],"research":[20],"has":[21],"specified":[22],"social":[23,79,123,152,206,239],"influence":[24,124,240],"to":[25,41,48,143,162,167,184,188,192,234],"be":[26],"one":[27],"of":[28,98,122,205,225,238],"the":[29,50,58,64,69,99,119,150,164,168,186,216,226],"most":[30],"reasons":[32],"user":[34,46,252],"churn,":[35],"thereby":[37],"many":[38],"works":[39,55],"start":[40],"model":[42,144,169,187],"its":[43],"effects":[44],"on":[45,198],"improve":[49],"performance.":[52],"However,":[53],"existing":[54,100],"only":[56],"use":[57],"data's":[59],"correlational":[60],"information":[61,121,166,191,237],"while":[62],"neglecting":[63],"problem's":[65],"causal":[66,120,165,190,236],"nature.":[67],"Specifically,":[68,131],"fact":[70],"that":[71,138],"a":[72,108,135,157,179],"user's":[73],"correlated":[76],"with":[77,202,215],"some":[78],"factors":[80],"does":[81],"not":[82],"mean":[83],"he/she":[84],"actually":[86],"influenced":[87],"by":[88,170],"his/her":[89],"friends,":[90],"which":[91,115,246],"results":[92,228],"in":[93],"inaccurate":[94],"unexplainable":[96],"predictions":[97],"methods.":[101],"To":[102],"bridge":[103],"this":[104],"gap,":[105],"we":[106,132,155,177],"develop":[107],"counterfactual":[109,158,174,181],"modeling":[110],"framework":[111,137,183],"prediction,":[114],"can":[116],"effectively":[117],"capture":[118,235],"accurate":[126],"explainable":[128,243],"predictions.":[130],"first":[133],"propose":[134,156],"backbone":[136],"uses":[139],"two":[140,199],"separate":[141],"embeddings":[142],"users'":[145],"endogenous":[146],"intentions":[148],"exogenous":[151],"influence.":[153],"Then,":[154],"data":[159],"augmentation":[160],"module":[161],"introduce":[163],"providing":[171],"partially":[172],"labeled":[173],"data.":[175],"Finally,":[176],"design":[178],"three-headed":[180],"guide":[185],"learn":[189],"facilitate":[193],"prediction.":[195],"Extensive":[196],"experiments":[197],"large-scale":[200],"datasets":[201],"different":[203],"types":[204],"relations":[207],"show":[208],"our":[209,230],"model's":[210],"superior":[211],"performance":[213],"compared":[214],"state-of-the-art":[217],"baselines.":[218],"We":[219],"further":[220],"conduct":[221],"an":[222],"in-depth":[223],"analysis":[224],"demonstrating":[229],"proposed":[231],"method's":[232],"ability":[233],"give":[242],"predictions,":[245],"provide":[247],"insights":[248],"into":[249],"designing":[250],"better":[251],"retention":[253],"strategies.":[254]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}