{"id":"https://openalex.org/W4288058308","doi":"https://doi.org/10.1145/3514094.3534142","title":"Towards Better Detection of Biased Language with Scarce, Noisy, and Biased Annotations","display_name":"Towards Better Detection of Biased Language with Scarce, Noisy, and Biased Annotations","publication_year":2022,"publication_date":"2022-07-26","ids":{"openalex":"https://openalex.org/W4288058308","doi":"https://doi.org/10.1145/3514094.3534142"},"language":"en","primary_location":{"id":"doi:10.1145/3514094.3534142","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3514094.3534142","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3514094.3534142","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3514094.3534142","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5051008303","display_name":"Zhuoyan Li","orcid":"https://orcid.org/0000-0002-3094-7364"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zhuoyan Li","raw_affiliation_strings":["Purdue University, West Lafayette, IN, USA"],"affiliations":[{"raw_affiliation_string":"Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045282669","display_name":"Zhuoran Lu","orcid":"https://orcid.org/0000-0002-1079-2043"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhuoran Lu","raw_affiliation_strings":["Purdue University, West Lafayette, IN, USA"],"affiliations":[{"raw_affiliation_string":"Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071294124","display_name":"Ming Yin","orcid":"https://orcid.org/0000-0002-7364-139X"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ming Yin","raw_affiliation_strings":["Purdue University, West Lafayette, IN, USA"],"affiliations":[{"raw_affiliation_string":"Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5051008303"],"corresponding_institution_ids":["https://openalex.org/I219193219"],"apc_list":null,"apc_paid":null,"fwci":0.7954,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.76479344,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"411","last_page":"423"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12262","display_name":"Hate Speech and Cyberbullying Detection","score":0.9995999932289124,"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/T12262","display_name":"Hate Speech and Cyberbullying Detection","score":0.9995999932289124,"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/T10028","display_name":"Topic Modeling","score":0.9944000244140625,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.987500011920929,"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":0.8088333606719971},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.7285710573196411},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5830088257789612},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5274702906608582},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.5213742852210999},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.48883217573165894},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4807550609111786},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.46714162826538086},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.4670844078063965},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.37019938230514526}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8088333606719971},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7285710573196411},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5830088257789612},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5274702906608582},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.5213742852210999},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.48883217573165894},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4807550609111786},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.46714162826538086},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.4670844078063965},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.37019938230514526},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3514094.3534142","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3514094.3534142","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3514094.3534142","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3514094.3534142","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3514094.3534142","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3514094.3534142","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.7400000095367432}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4288058308.pdf","grobid_xml":"https://content.openalex.org/works/W4288058308.grobid-xml"},"referenced_works_count":41,"referenced_works":["https://openalex.org/W2038201841","https://openalex.org/W2077866444","https://openalex.org/W2088622183","https://openalex.org/W2128669672","https://openalex.org/W2187089797","https://openalex.org/W2524182563","https://openalex.org/W2758097047","https://openalex.org/W2791170418","https://openalex.org/W2811306785","https://openalex.org/W2889624842","https://openalex.org/W2901215301","https://openalex.org/W2955497741","https://openalex.org/W2962787423","https://openalex.org/W2962917899","https://openalex.org/W2962977603","https://openalex.org/W2963526187","https://openalex.org/W2963667126","https://openalex.org/W2971296908","https://openalex.org/W2979826702","https://openalex.org/W2999905431","https://openalex.org/W3006260012","https://openalex.org/W3033129824","https://openalex.org/W3035524453","https://openalex.org/W3096655658","https://openalex.org/W3102391629","https://openalex.org/W3159630167","https://openalex.org/W3172399575","https://openalex.org/W3173190788","https://openalex.org/W3173783447","https://openalex.org/W3174036215","https://openalex.org/W3174685870","https://openalex.org/W3175741278","https://openalex.org/W3192247156","https://openalex.org/W3196579898","https://openalex.org/W3210812898","https://openalex.org/W3213844504","https://openalex.org/W4238846128","https://openalex.org/W4255386139","https://openalex.org/W4287807502","https://openalex.org/W4288310870","https://openalex.org/W6600120041"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W4321353415","https://openalex.org/W2745001401","https://openalex.org/W3204418343","https://openalex.org/W1560624709","https://openalex.org/W1996537998","https://openalex.org/W3214142563","https://openalex.org/W3166286441","https://openalex.org/W4221162086","https://openalex.org/W3111760155"],"abstract_inverted_index":{"Biased":[0],"language":[1,45,73,109,122,171],"is":[2,21,31,47,156],"prevalent":[3],"in":[4,111,178],"today's":[5],"online":[6,14],"social":[7],"media.":[8],"To":[9],"reduce":[10],"the":[11,37,120,129,140,145,151,168,183,186,189],"amount":[12],"of":[13,128,180,188],"biased":[15,26,44,61,72,108,121,170],"language,":[16,27],"one":[17],"critical":[18],"first":[19],"step":[20],"to":[22,118,167],"accurately":[23],"detect":[24],"such":[25],"ideally":[28],"automatically.":[29],"This":[30],"a":[32,43,103,125,134],"challenging":[33],"problem,":[34,137],"however,":[35],"as":[36],"annotated":[38],"data":[39,131,153],"necessary":[40],"for":[41,107],"training":[42],"classifier":[46,74],"either":[48],"scarce":[49],"and":[50,59,84,185],"costly":[51],"(e.g.,":[52,65,87],"when":[53,66],"collected":[54,67],"from":[55,68],"experts),":[56],"or":[57],"noisy":[58],"potentially":[60],"on":[62,77,174],"their":[63],"own":[64],"crowd":[69],"workers).":[70],"The":[71],"built":[75],"based":[76],"these":[78],"annotations":[79],"may":[80],"thus":[81],"be":[82],"inaccurate,":[83],"sometimes":[85],"unfair":[86],"have":[88],"systematic":[89],"accuracy":[90,184],"disparities":[91],"across":[92],"texts":[93],"with":[94],"different":[95],"political":[96],"leanings).":[97],"In":[98],"this":[99],"paper,":[100],"we":[101,113],"propose":[102],"novel":[104],"method,":[105],"CLEARE,":[106],"detection,":[110],"which":[112],"utilize":[114],"self-supervised":[115],"contrastive":[116],"learning":[117],"enhance":[119],"classifier---we":[123],"learn":[124],"robust":[126],"encoder":[127,141],"textual":[130],"through":[132],"solving":[133],"min-max":[135],"optimization":[136],"so":[138],"that":[139,161],"could":[142],"help":[143],"achieve":[144],"best":[146],"classification":[147],"performance":[148],"even":[149],"if":[150],"worst":[152],"augmentation":[154],"strategy":[155],"selected.":[157],"Extensive":[158],"evaluations":[159],"suggest":[160],"CLEARE":[162],"shows":[163],"substantial":[164],"improvements":[165],"compared":[166],"state-of-art":[169],"detection":[172],"methods":[173],"several":[175],"benchmark":[176],"datasets,":[177],"terms":[179],"improving":[181],"both":[182],"fairness":[187],"detection.":[190]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
