{"id":"https://openalex.org/W4416078568","doi":"https://doi.org/10.1145/3746252.3760800","title":"Improving Content Anomaly Detection on Social Media via Counterfactual Mitigation of Social Event-Induced Bias","display_name":"Improving Content Anomaly Detection on Social Media via Counterfactual Mitigation of Social Event-Induced Bias","publication_year":2025,"publication_date":"2025-11-10","ids":{"openalex":"https://openalex.org/W4416078568","doi":"https://doi.org/10.1145/3746252.3760800"},"language":null,"primary_location":{"id":"doi:10.1145/3746252.3760800","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3746252.3760800","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3746252.3760800","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 34th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3746252.3760800","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Jiaxin Li","orcid":"https://orcid.org/0009-0009-6910-8005"},"institutions":[{"id":"https://openalex.org/I12393601","display_name":"Huaihua University","ror":"https://ror.org/04zn6xq74","country_code":"CN","type":"education","lineage":["https://openalex.org/I12393601"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaxin Li","raw_affiliation_strings":["Huaihua University, Huaihua, Hunan, China"],"raw_orcid":"https://orcid.org/0009-0009-6910-8005","affiliations":[{"raw_affiliation_string":"Huaihua University, Huaihua, Hunan, China","institution_ids":["https://openalex.org/I12393601"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100867302","display_name":"Geng Zhao","orcid":"https://orcid.org/0009-0003-7037-805X"},"institutions":[{"id":"https://openalex.org/I223822909","display_name":"Heidelberg University","ror":"https://ror.org/038t36y30","country_code":"DE","type":"education","lineage":["https://openalex.org/I223822909"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Geng Zhao","raw_affiliation_strings":["ICL, Heidelberg University, Heidelberg, BW, Germany"],"raw_orcid":"https://orcid.org/0009-0003-7037-805X","affiliations":[{"raw_affiliation_string":"ICL, Heidelberg University, Heidelberg, BW, Germany","institution_ids":["https://openalex.org/I223822909"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.37841565,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4935","last_page":"4939"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11147","display_name":"Misinformation and Its Impacts","score":0.6302000284194946,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"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/T11147","display_name":"Misinformation and Its Impacts","score":0.6302000284194946,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"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/T11644","display_name":"Spam and Phishing Detection","score":0.09019999951124191,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.035100001841783524,"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/counterfactual-thinking","display_name":"Counterfactual thinking","score":0.7448999881744385},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.6154999732971191},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.39070001244544983},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.3765999972820282},{"id":"https://openalex.org/keywords/user-generated-content","display_name":"User-generated content","score":0.34610000252723694}],"concepts":[{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.7448999881744385},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.6154999732971191},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4652999937534332},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.39070001244544983},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.3765999972820282},{"id":"https://openalex.org/C101293273","wikidata":"https://www.wikidata.org/wiki/Q579716","display_name":"User-generated content","level":3,"score":0.34610000252723694},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.34290000796318054},{"id":"https://openalex.org/C2778152352","wikidata":"https://www.wikidata.org/wiki/Q5165061","display_name":"Content (measure theory)","level":2,"score":0.34279999136924744},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.3183000087738037},{"id":"https://openalex.org/C108827166","wikidata":"https://www.wikidata.org/wiki/Q175975","display_name":"Internet privacy","level":1,"score":0.304500013589859},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.2815999984741211},{"id":"https://openalex.org/C2781426361","wikidata":"https://www.wikidata.org/wiki/Q5326940","display_name":"Earnings","level":2,"score":0.26579999923706055},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.25870001316070557},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.25839999318122864},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.25690001249313354},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.25600001215934753},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.2547999918460846}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3746252.3760800","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3746252.3760800","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3746252.3760800","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 34th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3746252.3760800","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3746252.3760800","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3746252.3760800","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 34th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4416078568.pdf","grobid_xml":"https://content.openalex.org/works/W4416078568.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W2003905926","https://openalex.org/W2079026667","https://openalex.org/W2143117649","https://openalex.org/W2250734828","https://openalex.org/W2742330194","https://openalex.org/W2758474413","https://openalex.org/W2793897830","https://openalex.org/W3012650537","https://openalex.org/W3097590906","https://openalex.org/W3097679710","https://openalex.org/W3101767999","https://openalex.org/W3152876231","https://openalex.org/W3175294292","https://openalex.org/W3176001432","https://openalex.org/W3177101259","https://openalex.org/W3200739262","https://openalex.org/W3210022786","https://openalex.org/W4220848927","https://openalex.org/W4221168025","https://openalex.org/W4224309172","https://openalex.org/W4224316507","https://openalex.org/W4283796213","https://openalex.org/W4296591844","https://openalex.org/W4385570415","https://openalex.org/W4385570504","https://openalex.org/W4385571026","https://openalex.org/W4385571544","https://openalex.org/W4385893817","https://openalex.org/W4389524202","https://openalex.org/W4402727075"],"related_works":[],"abstract_inverted_index":{"Content":[0],"anomaly":[1,37,144,167],"detection":[2],"on":[3,122,128],"social":[4,21,68,101,140,154,172],"media":[5],"(SNS)":[6],"plays":[7,146],"a":[8,32,56,73,82,147,150],"critical":[9],"role":[10,152],"in":[11,38,169],"maintaining":[12],"healthy":[13],"online":[14],"communities.However,":[15],"the":[16,44,63,87,94,97,100,108,111,114,162],"prevalence":[17],"of":[18,133,164],"major":[19,139],"real-world":[20],"events":[22],"can":[23],"introduce":[24],"model":[25],"bias":[26,64,88],"that":[27,91,158],"skews,":[28],"narrows,":[29],"and":[30,42,77,99,113,149],"undermines":[31],"detector's":[33],"ability":[34],"to":[35,61],"perceive":[36],"content":[39,143,166],"by":[40,66],"contaminating":[41],"homogenizing":[43],"expressions":[45],"posted":[46],"during":[47,124],"these":[48],"events.To":[49],"address":[50],"this":[51],"challenge,":[52],"we":[53],"propose":[54],"SeiNS,":[55],"novel,":[57],"model-agnostic":[58],"plugin":[59],"designed":[60],"mitigate":[62],"induced":[65],"prevalent":[67],"events.SeiNS":[69],"comprises":[70],"two":[71,129],"components:":[72],"Social":[74],"Event":[75,79],"Extractor":[76],"an":[78],"Involvement":[80],"Perceptor.For":[81],"given":[83],"post,":[84],"SeiNS":[85,127,159],"removes":[86],"through":[89],"steps":[90],"include":[92],"treating":[93],"correlation":[95,109],"between":[96,110],"label":[98,112],"event-induced":[102],"homogenized":[103],"content,":[104],"as":[105,107,117],"well":[106],"event-involvement":[115],"representation,":[116],"spurious;":[118],"performing":[119],"counterfactual":[120],"learning":[121],"them":[123],"fine-tuning.We":[125],"evaluate":[126],"benchmark":[130],"datasets":[131],"composed":[132],"real":[134],"SNS":[135,165],"posts":[136],"under":[137],"various":[138],"events,":[141],"where":[142],"respectively":[145],"negative":[148],"positive":[151],"for":[153],"good.The":[155],"results":[156],"show":[157],"significantly":[160],"improves":[161],"robustness":[163],"detectors":[168],"dynamic-even":[170],"unstable-online":[171],"environments.":[173]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-11-10T00:00:00"}