{"id":"https://openalex.org/W3035101152","doi":"https://doi.org/10.24963/ijcai.2020/622","title":"FinBERT: A Pre-trained Financial Language Representation Model for Financial Text Mining","display_name":"FinBERT: A Pre-trained Financial Language Representation Model for Financial Text Mining","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3035101152","doi":"https://doi.org/10.24963/ijcai.2020/622","mag":"3035101152"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2020/622","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2020/622","pdf_url":"https://www.ijcai.org/proceedings/2020/0622.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2020/0622.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100452098","display_name":"Zhuang Liu","orcid":"https://orcid.org/0000-0002-4695-6345"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhuang Liu","raw_affiliation_strings":["Dalian University of Technology, Dalian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046871248","display_name":"Degen Huang","orcid":"https://orcid.org/0000-0002-8860-7805"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Degen Huang","raw_affiliation_strings":["Dalian University of Technology, Dalian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031577422","display_name":"Kaiyu Huang","orcid":"https://orcid.org/0000-0001-6779-1810"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaiyu Huang","raw_affiliation_strings":["Dalian University of Technology, Dalian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017053450","display_name":"Zhuang Li","orcid":"https://orcid.org/0000-0001-7473-4056"},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuang Li","raw_affiliation_strings":["Union Mobile Financial Technology Co., Ltd., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Union Mobile Financial Technology Co., Ltd., Beijing, China","institution_ids":["https://openalex.org/I180662265"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110722665","display_name":"Jun Zhao","orcid":"https://orcid.org/0000-0003-3370-2263"},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]},{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Zhao","raw_affiliation_strings":["Union Mobile Financial Technology Co., Ltd., Beijing, China","Dalian University of Technology, Dalian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Union Mobile Financial Technology Co., Ltd., Beijing, China","institution_ids":["https://openalex.org/I180662265"]},{"raw_affiliation_string":"Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100452098"],"corresponding_institution_ids":["https://openalex.org/I27357992"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":283,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4513","last_page":"4519"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9988999962806702,"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/T10028","display_name":"Topic Modeling","score":0.9988999962806702,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.998199999332428,"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"}},{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9919000267982483,"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":0.7678673267364502},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7188037633895874},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6028296947479248},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5683853626251221},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5389803647994995},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4948102831840515},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45839983224868774},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.4199085831642151},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.4182214140892029}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7678673267364502},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7188037633895874},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6028296947479248},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5683853626251221},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5389803647994995},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4948102831840515},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45839983224868774},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.4199085831642151},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.4182214140892029},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2020/622","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2020/622","pdf_url":"https://www.ijcai.org/proceedings/2020/0622.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2020/622","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2020/622","pdf_url":"https://www.ijcai.org/proceedings/2020/0622.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.5699999928474426,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G6482782238","display_name":"\u57fa\u4e8e\u6df1\u5ea6\u5b66\u4e60\u7684\u53e5\u5b50\u76f8\u4f3c\u5ea6\u8ba1\u7b97\u7814\u7a76","funder_award_id":"61672127","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3035101152.pdf","grobid_xml":"https://content.openalex.org/works/W3035101152.grobid-xml"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W1546425147","https://openalex.org/W1614298861","https://openalex.org/W2271840356","https://openalex.org/W2622263826","https://openalex.org/W2763421725","https://openalex.org/W2798882116","https://openalex.org/W2888160375","https://openalex.org/W2896457183","https://openalex.org/W2938830017","https://openalex.org/W2945260553","https://openalex.org/W2950577311","https://openalex.org/W2962739339","https://openalex.org/W2963341956","https://openalex.org/W2963403868","https://openalex.org/W2963854351","https://openalex.org/W2965373594","https://openalex.org/W2970636124","https://openalex.org/W2971274815","https://openalex.org/W2996428491","https://openalex.org/W2997200074","https://openalex.org/W3011411500","https://openalex.org/W3029462071","https://openalex.org/W3123756285","https://openalex.org/W4288089799","https://openalex.org/W4300485781","https://openalex.org/W4301239768","https://openalex.org/W4385245566"],"related_works":["https://openalex.org/W2366107444","https://openalex.org/W4388145910","https://openalex.org/W2381570729","https://openalex.org/W1976205134","https://openalex.org/W4248336175","https://openalex.org/W2031260042","https://openalex.org/W2391445434","https://openalex.org/W3009369890","https://openalex.org/W4312490297","https://openalex.org/W2062212388"],"abstract_inverted_index":{"There":[0],"is":[1,63,90],"growing":[2],"interest":[3],"in":[4,74],"the":[5,12,16,68,151],"tasks":[6,110],"of":[7,18,52,70,155,163],"financial":[8,41,60,75,99,120],"text":[9,42,61],"mining.":[10],"Over":[11],"past":[13],"few":[14],"years,":[15],"progress":[17,30],"Natural":[19],"Language":[20],"Processing":[21],"(NLP)":[22],"based":[23],"on":[24,40,97,116],"deep":[25,35,57],"learning":[26,36,58],"advanced":[27],"rapidly.":[28],"Significant":[29],"has":[31],"been":[32],"made":[33],"with":[34],"showing":[37],"promising":[38],"results":[39,137,149],"mining":[43,62],"models.":[44,146],"However,":[45],"as":[46],"NLP":[47],"models":[48,162],"require":[49],"large":[50],"amounts":[51],"labeled":[53,71],"training":[54,72],"data,":[55],"applying":[56],"to":[59,67,129],"often":[64],"unsuccessful":[65],"due":[66],"lack":[69],"data":[73],"fields.":[76],"To":[77],"address":[78],"this":[79],"issue,":[80],"we":[81,106],"present":[82],"FinBERT":[83,126,141,164],"(BERT":[84],"for":[85],"Financial":[86],"Text":[87],"Mining)":[88],"that":[89,139],"a":[91],"domain":[92,121],"specific":[93],"language":[94,131],"model":[95,127],"pre-trained":[96,161],"large-scale":[98],"corpora.":[100],"In":[101],"FinBERT,":[102],"different":[103],"from":[104],"BERT,":[105],"construct":[107],"six":[108],"pre-training":[109],"covering":[111],"more":[112],"knowledge,":[113],"simultaneously":[114],"trained":[115],"general":[117],"corpora":[118],"and":[119,133,153,160],"corpora,":[122],"which":[123],"can":[124],"enable":[125],"better":[128],"capture":[130],"knowledge":[132],"semantic":[134],"information.":[135],"The":[136,157],"show":[138],"our":[140],"outperforms":[142],"all":[143],"current":[144],"state-of-the-art":[145],"Extensive":[147],"experimental":[148],"demonstrate":[150],"effectiveness":[152],"robustness":[154],"FinBERT.":[156],"source":[158],"code":[159],"are":[165],"available":[166],"online.":[167]},"counts_by_year":[{"year":2026,"cited_by_count":31},{"year":2025,"cited_by_count":81},{"year":2024,"cited_by_count":55},{"year":2023,"cited_by_count":49},{"year":2022,"cited_by_count":43},{"year":2021,"cited_by_count":22},{"year":2020,"cited_by_count":2}],"updated_date":"2026-07-20T07:56:41.581041","created_date":"2025-10-10T00:00:00"}
