{"id":"https://openalex.org/W7124448822","doi":"https://doi.org/10.1108/jm2-08-2025-0415","title":"AI driven sentiment analysis in financial markets: using transformer base models and social media signals for stock market predictions","display_name":"AI driven sentiment analysis in financial markets: using transformer base models and social media signals for stock market predictions","publication_year":2026,"publication_date":"2026-01-16","ids":{"openalex":"https://openalex.org/W7124448822","doi":"https://doi.org/10.1108/jm2-08-2025-0415"},"language":"en","primary_location":{"id":"doi:10.1108/jm2-08-2025-0415","doi":"https://doi.org/10.1108/jm2-08-2025-0415","is_oa":false,"landing_page_url":"https://doi.org/10.1108/jm2-08-2025-0415","pdf_url":null,"source":{"id":"https://openalex.org/S15925821","display_name":"Journal of Modelling in Management","issn_l":"1746-5664","issn":["1746-5664","1746-5672"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-c","anvur-scientific","cwts-core","jufo-1","norway-1","poland-40","russia-white-list-2"],"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Modelling in Management","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"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/A5123221318","display_name":"Rashid Khalil","orcid":"https://orcid.org/0000-0002-2660-5812","observed_orcids":["https://orcid.org/0000-0002-2660-5812"]},"institutions":[{"id":"https://openalex.org/I73898932","display_name":"Bahrain Polytechnic","ror":"https://ror.org/01dv0vw10","country_code":"BH","type":"education","lineage":["https://openalex.org/I73898932"]}],"countries":["BH"],"is_corresponding":true,"raw_author_name":"Rashid Khalil","raw_affiliation_strings":["Bahrain Polytechnic Department of Banking and Finance, School of Business and Logistics, , Isa Town,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bahrain Polytechnic Department of Banking and Finance, School of Business and Logistics, , Isa Town,","institution_ids":["https://openalex.org/I73898932"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5123221318"],"corresponding_institution_ids":["https://openalex.org/I73898932"],"apc_list":null,"apc_paid":null,"fwci":54.8098,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.99893532,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"25"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":1.0,"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":1.0,"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/T10047","display_name":"Financial Markets and Investment Strategies","score":9.999999747378752e-05,"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"}},{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":9.999999747378752e-05,"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/sentiment-analysis","display_name":"sentiment analysis","score":0.921999990940094},{"id":"https://openalex.org/keywords/stock-price-prediction","display_name":"stock price prediction","score":0.8899999856948853},{"id":"https://openalex.org/keywords/social-media-sentiment","display_name":"social media sentiment","score":0.9160000085830688},{"id":"https://openalex.org/keywords/transformer","display_name":"transformer models","score":0.7889999747276306},{"id":"https://openalex.org/keywords/finbert","display_name":"FinBERT","score":0.9990000128746033},{"id":"https://openalex.org/keywords/granger-causality","display_name":"Granger causality","score":0.9570000171661377},{"id":"https://openalex.org/keywords/sectoral-differences","display_name":"sectoral differences","score":0.7369999885559082},{"id":"https://openalex.org/keywords/ai-governance","display_name":"AI governance","score":0.6660000085830688},{"id":"https://openalex.org/keywords/financial-markets","display_name":"financial markets","score":0.5479999780654907}],"concepts":[{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.753000020980835},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.554099977016449},{"id":"https://openalex.org/C2780299701","wikidata":"https://www.wikidata.org/wiki/Q475000","display_name":"Stock market","level":3,"score":0.5527999997138977},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.4797999858856201},{"id":"https://openalex.org/C19244329","wikidata":"https://www.wikidata.org/wiki/Q208697","display_name":"Financial market","level":2,"score":0.4551999866962433},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.453900009393692},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.41280001401901245},{"id":"https://openalex.org/C2780821815","wikidata":"https://www.wikidata.org/wiki/Q5340806","display_name":"Portfolio","level":2,"score":0.38679999113082886},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.37369999289512634},{"id":"https://openalex.org/C2780233690","wikidata":"https://www.wikidata.org/wiki/Q535347","display_name":"Transparency (behavior)","level":2,"score":0.3698999881744385},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3659999966621399},{"id":"https://openalex.org/C163068380","wikidata":"https://www.wikidata.org/wiki/Q3409313","display_name":"Economic forecasting","level":2,"score":0.361299991607666},{"id":"https://openalex.org/C129824826","wikidata":"https://www.wikidata.org/wiki/Q2630107","display_name":"Granger causality","level":2,"score":0.3610999882221222},{"id":"https://openalex.org/C75949130","wikidata":"https://www.wikidata.org/wiki/Q848010","display_name":"Database transaction","level":2,"score":0.3393000066280365},{"id":"https://openalex.org/C180706569","wikidata":"https://www.wikidata.org/wiki/Q13479982","display_name":"Cryptocurrency","level":2,"score":0.33219999074935913},{"id":"https://openalex.org/C97256817","wikidata":"https://www.wikidata.org/wiki/Q1462316","display_name":"Spurious relationship","level":2,"score":0.3285999894142151},{"id":"https://openalex.org/C139043278","wikidata":"https://www.wikidata.org/wiki/Q837171","display_name":"Financial services","level":2,"score":0.3269999921321869},{"id":"https://openalex.org/C155092808","wikidata":"https://www.wikidata.org/wiki/Q182557","display_name":"Computational linguistics","level":2,"score":0.3188000023365021},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.3156000077724457},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.310699999332428},{"id":"https://openalex.org/C186027771","wikidata":"https://www.wikidata.org/wiki/Q4008379","display_name":"Valuation (finance)","level":2,"score":0.3084000051021576},{"id":"https://openalex.org/C39389867","wikidata":"https://www.wikidata.org/wiki/Q380767","display_name":"Corporate governance","level":2,"score":0.3005000054836273},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.29670000076293945},{"id":"https://openalex.org/C24338571","wikidata":"https://www.wikidata.org/wiki/Q2566298","display_name":"Autoregressive integrated moving average","level":3,"score":0.2939000129699707},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.2827000021934509},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.28130000829696655},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2808000147342682},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.27619999647140503},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.26570001244544983},{"id":"https://openalex.org/C23925645","wikidata":"https://www.wikidata.org/wiki/Q5449731","display_name":"Financial modeling","level":2,"score":0.26409998536109924},{"id":"https://openalex.org/C98014903","wikidata":"https://www.wikidata.org/wiki/Q832161","display_name":"Financial ratio","level":2,"score":0.2572999894618988},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.25690001249313354},{"id":"https://openalex.org/C2988984586","wikidata":"https://www.wikidata.org/wiki/Q1020013","display_name":"Stock price","level":3,"score":0.251800000667572}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1108/jm2-08-2025-0415","doi":"https://doi.org/10.1108/jm2-08-2025-0415","is_oa":false,"landing_page_url":"https://doi.org/10.1108/jm2-08-2025-0415","pdf_url":null,"source":{"id":"https://openalex.org/S15925821","display_name":"Journal of Modelling in Management","issn_l":"1746-5664","issn":["1746-5664","1746-5672"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-c","anvur-scientific","cwts-core","jufo-1","norway-1","poland-40","russia-white-list-2"],"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Modelling in Management","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1940372886","https://openalex.org/W1981780459","https://openalex.org/W2016210396","https://openalex.org/W2067054705","https://openalex.org/W2093290362","https://openalex.org/W2131773668","https://openalex.org/W2169667133","https://openalex.org/W2624385633","https://openalex.org/W2896457183","https://openalex.org/W2911964244","https://openalex.org/W2953522645","https://openalex.org/W2969896603","https://openalex.org/W2970636124","https://openalex.org/W3005778784","https://openalex.org/W3014479273","https://openalex.org/W3018089439","https://openalex.org/W3047406366","https://openalex.org/W3115071066","https://openalex.org/W3118814972","https://openalex.org/W3124185353","https://openalex.org/W3124986135","https://openalex.org/W3126053622","https://openalex.org/W3135178882","https://openalex.org/W4211017739","https://openalex.org/W4281678431","https://openalex.org/W4290659886","https://openalex.org/W4293101166","https://openalex.org/W4293705360","https://openalex.org/W4296408613","https://openalex.org/W4366123589","https://openalex.org/W4390425234","https://openalex.org/W4391917187","https://openalex.org/W4398177871","https://openalex.org/W4404500196","https://openalex.org/W4404924340","https://openalex.org/W4407592435","https://openalex.org/W4410523827","https://openalex.org/W4411842738","https://openalex.org/W4412878191","https://openalex.org/W4413605667","https://openalex.org/W4414072869","https://openalex.org/W4414417468","https://openalex.org/W4415231227"],"related_works":["https://openalex.org/W7162463188","https://openalex.org/W4416342755","https://openalex.org/W4415430399","https://openalex.org/W7162313827","https://openalex.org/W7123261165","https://openalex.org/W7084182234","https://openalex.org/W4379539262","https://openalex.org/W4415016282","https://openalex.org/W7155603480","https://openalex.org/W7164043491"],"abstract_inverted_index":{"Purpose":[0],"This":[1,58,188,206],"study":[2,189],"aims":[3],"to":[4,67,102,125,166,180,195,230],"explore":[5],"the":[6,30,42,151,183],"predictive":[7,111],"role":[8],"of":[9,32,46],"artificial":[10],"intelligence":[11],"(AI)-driven":[12],"sentiment":[13,34,85,130,139,196,217],"analysis":[14,119,134,218],"in":[15,113,129,145,162,202,236],"financial":[16,51,203,238],"markets":[17],"by":[18],"developing":[19],"a":[20,61,110,159,209],"hybrid":[21,152],"long":[22],"short-term":[23,142],"memory\u2013Random":[24],"Forest":[25],"framework.":[26],"It":[27],"investigates":[28],"whether":[29],"integration":[31],"generative":[33],"signals":[35],"with":[36,150,240],"historical":[37],"market":[38],"data":[39,63,72],"can":[40],"enhance":[41],"accuracy":[43,121,157],"and":[44,50,83,90,120,147,158,175,199,219,228,245],"robustness":[45],"stock":[47,70,143],"price":[48,71],"forecasting":[49,212,226],"predictions":[52],"across":[53],"various":[54],"industry":[55],"sectors.":[56],"Design/methodology/approach":[57],"research":[59,207],"uses":[60],"multisource":[62],"set":[64],"from":[65,73,78,86],"2019":[66],"2024,":[68],"including":[69],"Yahoo":[74],"Finance,":[75],"macroeconomic":[76],"indicators":[77],"Federal":[79],"Reserve":[80],"Economic":[81],"Data":[82],"textual":[84],"Reddit,":[87],"Twitter,":[88],"Bloomberg":[89],"Reuters.":[91],"Transformer-based":[92],"natural":[93],"language":[94],"processing":[95],"models,":[96],"such":[97],"as":[98,109],"FinBERT,":[99],"are":[100,123],"used":[101,108],"quantify":[103],"sentiment,":[104,181],"which":[105],"is":[106],"then":[107],"feature":[112],"machine":[114],"learning":[115],"models.":[116],"Granger":[117,140],"causality":[118],"metrics":[122],"applied":[124],"evaluate":[126],"sectoral":[127],"variations":[128],"impact.":[131],"Findings":[132],"Empirical":[133],"reveals":[135],"that":[136,214],"social":[137],"media":[138],"causes":[141],"movements":[144],"technology":[146],"finance":[148],"sectors,":[149],"model":[153],"achieving":[154],"68.5%":[155],"directional":[156],"22%":[160],"reduction":[161],"prediction":[163],"error":[164],"compared":[165],"ARIMA":[167],"models":[168],"benchmarks.":[169],"In":[170],"contrast,":[171],"sectors":[172],"like":[173],"healthcare":[174],"energy":[176],"show":[177],"minimal":[178],"sensitivity":[179],"underscoring":[182],"need":[184],"for":[185,242],"domain-specific":[186],"strategies.":[187],"also":[190],"identifies":[191],"ethical":[192,231],"concerns":[193],"related":[194],"manipulation,":[197],"transparency":[198],"AI":[200,234],"governance":[201],"contexts.":[204],"Originality/value":[205],"introduces":[208],"reproducible,":[210],"cross-sectoral":[211],"framework":[213],"bridges":[215],"AI,":[216],"finance.":[220],"The":[221],"proposed":[222],"architecture":[223],"offers":[224],"practical":[225],"enhancements":[227],"contributes":[229],"discourse":[232],"on":[233],"use":[235],"high-stakes":[237],"environments,":[239],"implications":[241],"regulators,":[243],"analysts":[244],"portfolio":[246],"managers.":[247]},"counts_by_year":[{"year":2026,"cited_by_count":17},{"year":2024,"cited_by_count":1}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2026-01-17T00:00:00"}