{"id":"https://openalex.org/W4406458403","doi":"https://doi.org/10.1109/bigdata62323.2024.10825272","title":"An Evaluation of Large Language Models in Financial Sentiment Analysis","display_name":"An Evaluation of Large Language Models in Financial Sentiment Analysis","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4406458403","doi":"https://doi.org/10.1109/bigdata62323.2024.10825272"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata62323.2024.10825272","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825272","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-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/A5045830539","display_name":"Alphaeus Dmonte","orcid":"https://orcid.org/0009-0009-7896-5834"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Alphaeus Dmonte","raw_affiliation_strings":["George Mason University,Fairfax,VA,USA"],"affiliations":[{"raw_affiliation_string":"George Mason University,Fairfax,VA,USA","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007959861","display_name":"Eunmi Ko","orcid":"https://orcid.org/0000-0002-7280-5815"},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Eunmi Ko","raw_affiliation_strings":["Rochester Institute of Technology,Rochester,NY,USA"],"affiliations":[{"raw_affiliation_string":"Rochester Institute of Technology,Rochester,NY,USA","institution_ids":["https://openalex.org/I155173764"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024937008","display_name":"Marcos Zampieri","orcid":"https://orcid.org/0000-0002-2346-3847"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Marcos Zampieri","raw_affiliation_strings":["George Mason University,Fairfax,VA,USA"],"affiliations":[{"raw_affiliation_string":"George Mason University,Fairfax,VA,USA","institution_ids":["https://openalex.org/I162714631"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5045830539"],"corresponding_institution_ids":["https://openalex.org/I162714631"],"apc_list":null,"apc_paid":null,"fwci":4.3057,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.94663331,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"4869","last_page":"4874"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9991000294685364,"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"}},"topics":[{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9991000294685364,"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/T10028","display_name":"Topic Modeling","score":0.9961000084877014,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.995199978351593,"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":0.6899265646934509},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.5873806476593018},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.40304404497146606},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3403862714767456}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6899265646934509},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.5873806476593018},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.40304404497146606},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3403862714767456}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata62323.2024.10825272","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825272","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1546425147","https://openalex.org/W2297801999","https://openalex.org/W2750592395","https://openalex.org/W2750893234","https://openalex.org/W2751249453","https://openalex.org/W2766176255","https://openalex.org/W2768476704","https://openalex.org/W2798064797","https://openalex.org/W2798300760","https://openalex.org/W2798658104","https://openalex.org/W2896457183","https://openalex.org/W2962739339","https://openalex.org/W2963026768","https://openalex.org/W3013505582","https://openalex.org/W3123492911","https://openalex.org/W3123756285","https://openalex.org/W3125952890","https://openalex.org/W3172955029","https://openalex.org/W3185341429","https://openalex.org/W4249906708","https://openalex.org/W4298110867","https://openalex.org/W4300485781","https://openalex.org/W4307079201","https://openalex.org/W4317213979","https://openalex.org/W4361866125","https://openalex.org/W4379468930","https://openalex.org/W4382998379","https://openalex.org/W4382998416","https://openalex.org/W4389523787","https://openalex.org/W4399321666","https://openalex.org/W6755207826","https://openalex.org/W6767182473","https://openalex.org/W6779154463","https://openalex.org/W6797038041","https://openalex.org/W6847076894","https://openalex.org/W6850820320","https://openalex.org/W6852584927","https://openalex.org/W6858023062"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2548633793","https://openalex.org/W3013279174","https://openalex.org/W2941935829","https://openalex.org/W2596247554","https://openalex.org/W3132372214","https://openalex.org/W4224284088","https://openalex.org/W3204019825"],"abstract_inverted_index":{"Financial":[0],"sentiment":[1,27],"analysis":[2,28],"can":[3],"help":[4,10],"in":[5,48,76],"understanding":[6],"market":[7],"trends":[8],"and":[9,12,43,90,136],"organizations":[11],"individuals":[13],"make":[14],"important":[15],"business":[16],"decisions.":[17],"Several":[18],"machine":[19],"learning":[20,121],"approaches":[21,35],"have":[22,53,70],"been":[23,73],"used":[24],"for":[25,60],"financial":[26,78],"over":[29],"the":[30,37,55,77,85,102,125,132],"years":[31],"ranging":[32],"from":[33,101],"lexicon-based":[34],"to":[36,116],"use":[38,56,108],"of":[39,57,87,98,128],"deep":[40],"neural":[41],"networks":[42],"transformer-based":[44],"models.":[45],"Recent":[46],"advances":[47],"Large":[49],"Language":[50,63],"Models":[51],"(LLM)":[52],"prompted":[54],"these":[58,68,129],"models":[59,69,130,135],"various":[61,88],"Natural":[62],"Processing":[64],"(NLP)":[65],"tasks,":[66],"however,":[67],"not":[71],"yet":[72],"substantially":[74],"explored":[75],"domain.":[79],"In":[80],"this":[81,109],"paper,":[82],"we":[83,91],"evaluate":[84,117],"performance":[86],"LLMs":[89,118],"introduce":[92],"a":[93],"small":[94],"benchmark":[95],"dataset":[96,110],"consisting":[97],"excerpts":[99],"extracted":[100],"Federal":[103],"Reserve":[104],"chair\u2019s":[105],"speeches.":[106],"We":[107,123],"along":[111],"with":[112,131],"other":[113],"existing":[114],"datasets":[115],"using":[119],"in-context":[120],"approaches.":[122],"compare":[124],"F1":[126],"scores":[127],"state-of-the-art":[133],"BERT-based":[134],"analyze":[137],"our":[138],"results.":[139]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8}],"updated_date":"2026-04-12T07:58:50.170612","created_date":"2025-10-10T00:00:00"}
