{"id":"https://openalex.org/W4404172054","doi":"https://doi.org/10.1145/3694860.3694870","title":"Predicting Stock Prices with FinBERT-LSTM: Integrating News Sentiment Analysis","display_name":"Predicting Stock Prices with FinBERT-LSTM: Integrating News Sentiment Analysis","publication_year":2024,"publication_date":"2024-08-15","ids":{"openalex":"https://openalex.org/W4404172054","doi":"https://doi.org/10.1145/3694860.3694870"},"language":"en","primary_location":{"id":"doi:10.1145/3694860.3694870","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3694860.3694870","pdf_url":null,"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 2024 8th International Conference on Cloud and Big Data Computing","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3694860.3694870","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5112300519","display_name":"W. Y. Gu","orcid":null},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wen jun Gu","raw_affiliation_strings":["Carey Business School, Johns Hopkins University, Baltimore, MD, USA"],"raw_orcid":"https://orcid.org/0009-0001-3043-8973","affiliations":[{"raw_affiliation_string":"Carey Business School, Johns Hopkins University, Baltimore, MD, USA","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yi hao Zhong","orcid":"https://orcid.org/0009-0009-5033-5806"},"institutions":[{"id":"https://openalex.org/I36672615","display_name":"Courant Institute of Mathematical Sciences","ror":"https://ror.org/037tm7f56","country_code":"US","type":"education","lineage":["https://openalex.org/I36672615","https://openalex.org/I57206974"]},{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yi hao Zhong","raw_affiliation_strings":["Courant Institute of Mathematical Sciences, New York University, New York, NY, USA"],"raw_orcid":"https://orcid.org/0009-0009-5033-5806","affiliations":[{"raw_affiliation_string":"Courant Institute of Mathematical Sciences, New York University, New York, NY, USA","institution_ids":["https://openalex.org/I36672615","https://openalex.org/I57206974"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Shi zun Li","orcid":"https://orcid.org/0009-0001-4826-6559"},"institutions":[{"id":"https://openalex.org/I149530613","display_name":"Lynn University","ror":"https://ror.org/04nqv0v23","country_code":"US","type":"education","lineage":["https://openalex.org/I149530613"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shi zun Li","raw_affiliation_strings":["Independent Researcher, Lynnwood, D.C., USA"],"raw_orcid":"https://orcid.org/0009-0001-4826-6559","affiliations":[{"raw_affiliation_string":"Independent Researcher, Lynnwood, D.C., USA","institution_ids":["https://openalex.org/I149530613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004959530","display_name":"Chang song Wei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chang song Wei","raw_affiliation_strings":["Digital Financial Information Technology Co. LTD, Chengdu, Sichuan, China"],"raw_orcid":"https://orcid.org/0009-0008-8898-9189","affiliations":[{"raw_affiliation_string":"Digital Financial Information Technology Co. LTD, Chengdu, Sichuan, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Li ting Dong","orcid":"https://orcid.org/0009-0004-3214-5279"},"institutions":[{"id":"https://openalex.org/I178169726","display_name":"Southern Methodist University","ror":"https://ror.org/042tdr378","country_code":"US","type":"education","lineage":["https://openalex.org/I178169726"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Li ting Dong","raw_affiliation_strings":["Cox School of Business, Southern Methodist University, Dallas, TX, USA"],"raw_orcid":"https://orcid.org/0009-0004-3214-5279","affiliations":[{"raw_affiliation_string":"Cox School of Business, Southern Methodist University, Dallas, TX, USA","institution_ids":["https://openalex.org/I178169726"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005636812","display_name":"Zhuoyue Wang","orcid":"https://orcid.org/0009-0000-4350-5584"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhuo yue Wang","raw_affiliation_strings":["Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, USA"],"raw_orcid":"https://orcid.org/0009-0000-4350-5584","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100308886","display_name":"Chao Yan","orcid":"https://orcid.org/0009-0005-4223-6956"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chao Yan","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, USA"],"raw_orcid":"https://orcid.org/0009-0005-4223-6956","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, USA","institution_ids":["https://openalex.org/I12912129"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":28.2338,"has_fulltext":true,"cited_by_count":70,"citation_normalized_percentile":{"value":0.99812566,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"67","last_page":"72"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9998999834060669,"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":0.9998999834060669,"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.9922000169754028,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10047","display_name":"Financial Markets and Investment Strategies","score":0.9829000234603882,"subfield":{"id":"https://openalex.org/subfields/2003","display_name":"Finance"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.7462447881698608},{"id":"https://openalex.org/keywords/stock","display_name":"Stock (firearms)","score":0.5980371236801147},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5960793495178223},{"id":"https://openalex.org/keywords/stock-price","display_name":"Stock price","score":0.46016332507133484},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4083189368247986},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.33679741621017456},{"id":"https://openalex.org/keywords/history","display_name":"History","score":0.110383540391922},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.09435927867889404},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.07071468234062195}],"concepts":[{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.7462447881698608},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.5980371236801147},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5960793495178223},{"id":"https://openalex.org/C2988984586","wikidata":"https://www.wikidata.org/wiki/Q1020013","display_name":"Stock price","level":3,"score":0.46016332507133484},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4083189368247986},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.33679741621017456},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.110383540391922},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.09435927867889404},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.07071468234062195},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3694860.3694870","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3694860.3694870","pdf_url":null,"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 2024 8th International Conference on Cloud and Big Data Computing","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2407.16150","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2407.16150","pdf_url":"https://arxiv.org/pdf/2407.16150","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1145/3694860.3694870","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3694860.3694870","pdf_url":null,"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 2024 8th International Conference on Cloud and Big Data Computing","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.5199999809265137,"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1981276685","https://openalex.org/W2001926729","https://openalex.org/W2607162077","https://openalex.org/W2774559076","https://openalex.org/W2790354057","https://openalex.org/W3022746105","https://openalex.org/W3080733778","https://openalex.org/W4313502727","https://openalex.org/W4387847128","https://openalex.org/W4388824800","https://openalex.org/W4399878321","https://openalex.org/W4400240895","https://openalex.org/W4400585812","https://openalex.org/W4403211162","https://openalex.org/W6858035746","https://openalex.org/W6949129192"],"related_works":["https://openalex.org/W3204019825","https://openalex.org/W247222457","https://openalex.org/W1488120909","https://openalex.org/W3124131549","https://openalex.org/W2152348935","https://openalex.org/W2887069341","https://openalex.org/W2554106722","https://openalex.org/W1797892342","https://openalex.org/W4240248738","https://openalex.org/W3008476150"],"abstract_inverted_index":{"The":[0,55,230],"stock":[1,36,59,84,99,163,171,178,180,193],"market's":[2,179],"ascent":[3],"typically":[4],"mirrors":[5],"the":[6,10,49,68,81,103,114,129,141,151,162,177,184,197,217,221,227,236],"flourishing":[7],"state":[8],"of":[9,19,51,58,83,88,105,226,248],"economy,":[11],"whereas":[12],"its":[13],"decline":[14],"is":[15],"often":[16],"an":[17,20],"indicator":[18],"economic":[21],"downturn.":[22],"Therefore,":[23],"for":[24,31,187,220],"a":[25,119],"long":[26],"time,":[27],"significant":[28],"correlation":[29],"elements":[30],"predicting":[32],"trends":[33],"in":[34,48,183,246],"financial":[35,52,69,132],"markets":[37],"have":[38],"been":[39],"widely":[40],"discussed,":[41],"and":[42,86,170,195,203,214,223,241],"people":[43],"are":[44],"becoming":[45],"increasingly":[46],"interested":[47],"task":[50],"text":[53],"mining.":[54],"inherent":[56],"instability":[57],"prices":[60,85],"makes":[61],"them":[62],"acutely":[63],"responsive":[64],"to":[65,97,127,161],"fluctuations":[66],"within":[67,131],"markets.":[70],"In":[71],"this":[72,137],"article,":[73],"we":[74,135],"use":[75],"deep":[76],"learning":[77],"networks,":[78],"based":[79],"on":[80,199],"history":[82],"articles":[87],"financial,":[89],"business,":[90],"technical":[91],"news":[92,111,158,173,201],"that":[93,233],"introduce":[94],"market":[95,164],"information":[96],"predict":[98],"prices.":[100],"We":[101,117,189],"illustrate":[102],"enhancement":[104],"predictive":[106],"precision":[107],"by":[108,139,239],"integrating":[109],"weighted":[110],"categories":[112,159],"into":[113],"forecasting":[115],"model.":[116,154],"developed":[118],"pre-trained":[120],"NLP":[121],"model":[122,138,156,198,243],"known":[123],"as":[124,216],"FinBERT,":[125],"designed":[126],"discern":[128],"sentiments":[130],"texts.":[133],"Subsequently,":[134],"advanced":[136],"incorporating":[140],"sophisticated":[142],"Long":[143],"Short":[144],"Term":[145],"Memory":[146],"(LSTM)":[147],"architecture,":[148],"thus":[149],"constructing":[150],"innovative":[152],"FinBERT-LSTM":[153,234],"This":[155],"utilizes":[157],"related":[160,172],"structure":[165],"hierarchy,":[166],"namely":[167],"market,":[168],"industry,":[169],"categories,":[174],"combined":[175],"with":[176],"price":[181],"situation":[182],"previous":[185],"week":[186],"prediction.":[188],"selected":[190],"NASDAQ-100":[191],"index":[192],"data":[194],"trained":[196],"Benzinga":[200],"articles,":[202],"utilized":[204],"Mean":[205,209],"Absolute":[206,210],"Error":[207,212],"(MAE),":[208],"Percentage":[211],"(MAPE),":[213],"Accuracy":[215],"key":[218],"metrics":[219],"assessment":[222],"comparative":[224],"analysis":[225],"model's":[228],"performance.":[229],"results":[231],"indicate":[232],"performs":[235],"best,":[237],"followed":[238],"LSTM,":[240],"DNN":[242],"ranks":[244],"third":[245],"terms":[247],"effectiveness.":[249]},"counts_by_year":[{"year":2026,"cited_by_count":12},{"year":2025,"cited_by_count":42},{"year":2024,"cited_by_count":16}],"updated_date":"2026-07-03T08:13:44.112507","created_date":"2025-10-10T00:00:00"}