{"id":"https://openalex.org/W4406481236","doi":"https://doi.org/10.1080/12460125.2024.2440024","title":"Improving emotion estimation through a combination of ChatGPT and deep learning","display_name":"Improving emotion estimation through a combination of ChatGPT and deep learning","publication_year":2025,"publication_date":"2025-01-02","ids":{"openalex":"https://openalex.org/W4406481236","doi":"https://doi.org/10.1080/12460125.2024.2440024"},"language":"en","primary_location":{"id":"doi:10.1080/12460125.2024.2440024","is_oa":false,"landing_page_url":"https://doi.org/10.1080/12460125.2024.2440024","pdf_url":null,"source":{"id":"https://openalex.org/S119153320","display_name":"Journal of Decision System","issn_l":"1246-0125","issn":["1246-0125","2116-7052"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Decision Systems","raw_type":"journal-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/A5023895982","display_name":"Yusuke Sekine","orcid":"https://orcid.org/0009-0003-5444-5523"},"institutions":[{"id":"https://openalex.org/I8488066","display_name":"Chiba Institute of Technology","ror":"https://ror.org/00qwnam72","country_code":"JP","type":"education","lineage":["https://openalex.org/I8488066"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yusuke Sekine","raw_affiliation_strings":["Graduate School of Information and Computer Science, Chiba Institute of Technology, Narashino, Japan"],"raw_orcid":"https://orcid.org/0009-0003-5444-5523","affiliations":[{"raw_affiliation_string":"Graduate School of Information and Computer Science, Chiba Institute of Technology, Narashino, Japan","institution_ids":["https://openalex.org/I8488066"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082126895","display_name":"Seiji Kasuya","orcid":"https://orcid.org/0000-0002-5777-2437"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Seiji Kasuya","raw_affiliation_strings":["Advanced Research Center for Human Sciences, Waseda University, Tokorozawa, Japan"],"raw_orcid":"https://orcid.org/0000-0002-5777-2437","affiliations":[{"raw_affiliation_string":"Advanced Research Center for Human Sciences, Waseda University, Tokorozawa, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012681689","display_name":"Kiichi Tago","orcid":"https://orcid.org/0000-0003-2069-3759"},"institutions":[{"id":"https://openalex.org/I8488066","display_name":"Chiba Institute of Technology","ror":"https://ror.org/00qwnam72","country_code":"JP","type":"education","lineage":["https://openalex.org/I8488066"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Kiichi Tago","raw_affiliation_strings":["Graduate School of Information and Computer Science, Chiba Institute of Technology, Narashino, Japan"],"raw_orcid":"https://orcid.org/0000-0003-2069-3759","affiliations":[{"raw_affiliation_string":"Graduate School of Information and Computer Science, Chiba Institute of Technology, Narashino, Japan","institution_ids":["https://openalex.org/I8488066"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5012681689"],"corresponding_institution_ids":["https://openalex.org/I8488066"],"apc_list":null,"apc_paid":null,"fwci":4.188,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.93027695,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"34","issue":"1","first_page":"1","last_page":"18"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9993000030517578,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9993000030517578,"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/T10667","display_name":"Emotion and Mood Recognition","score":0.9951000213623047,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12488","display_name":"Mental Health via Writing","score":0.9940999746322632,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5267148613929749},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.5103101134300232},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5021638870239258},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.49048134684562683},{"id":"https://openalex.org/keywords/cognitive-psychology","display_name":"Cognitive psychology","score":0.35691606998443604},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.347810298204422},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3243340253829956},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.13667407631874084},{"id":"https://openalex.org/keywords/management","display_name":"Management","score":0.07322785258293152}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5267148613929749},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.5103101134300232},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5021638870239258},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.49048134684562683},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.35691606998443604},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.347810298204422},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3243340253829956},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.13667407631874084},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.07322785258293152}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/12460125.2024.2440024","is_oa":false,"landing_page_url":"https://doi.org/10.1080/12460125.2024.2440024","pdf_url":null,"source":{"id":"https://openalex.org/S119153320","display_name":"Journal of Decision System","issn_l":"1246-0125","issn":["1246-0125","2116-7052"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Decision Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1777859530","https://openalex.org/W2108765529","https://openalex.org/W2339570520","https://openalex.org/W2562781711","https://openalex.org/W2735459586","https://openalex.org/W2741036097","https://openalex.org/W2765739996","https://openalex.org/W2804489024","https://openalex.org/W2896457183","https://openalex.org/W2923490508","https://openalex.org/W2954107114","https://openalex.org/W2960022945","https://openalex.org/W3039449417","https://openalex.org/W3096230989","https://openalex.org/W3114191622","https://openalex.org/W3121163724","https://openalex.org/W3171376656","https://openalex.org/W3197373672","https://openalex.org/W4226026750","https://openalex.org/W4285210896","https://openalex.org/W4287994132","https://openalex.org/W4313028924","https://openalex.org/W4362564815","https://openalex.org/W4362565045","https://openalex.org/W4364385323","https://openalex.org/W4367353919","https://openalex.org/W4380536907","https://openalex.org/W4382935560","https://openalex.org/W4384158234","https://openalex.org/W4385245566","https://openalex.org/W4385302156","https://openalex.org/W4385338706","https://openalex.org/W4389312706","https://openalex.org/W6638025348","https://openalex.org/W6742810063"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W2961085424","https://openalex.org/W3215138031","https://openalex.org/W4306674287","https://openalex.org/W3009238340","https://openalex.org/W4360585206","https://openalex.org/W4321369474","https://openalex.org/W4285208911","https://openalex.org/W4387369504","https://openalex.org/W3046775127"],"abstract_inverted_index":{"Estimating":[0],"emotions":[1,91],"from":[2],"text":[3],"is":[4],"essential":[5],"for":[6,25,43,55,89,140],"machines":[7],"to":[8,18,110],"make":[9],"human-like":[10],"decisions,":[11],"but":[12],"it":[13],"remains":[14],"a":[15,101,137],"challenge":[16],"due":[17],"the":[19,57,77],"significant":[20],"time":[21],"and":[22,133],"manpower":[23],"required":[24],"labeling":[26],"training":[27,35],"data.":[28],"Accurate":[29],"machine":[30,141],"learning":[31,108,142],"relies":[32],"on":[33],"high-quality":[34],"data,":[36],"often":[37],"necessitating":[38],"multiple":[39],"rounds":[40],"of":[41,79],"evaluation":[42],"emotion":[44,82,126,145],"annotation.":[45],"Large":[46],"Language":[47],"Models":[48],"(LLMs),":[49],"such":[50],"as":[51],"ChatGPT,":[52],"hold":[53],"promise":[54],"reducing":[56],"labor":[58],"involved":[59],"in":[60,81,115,144],"this":[61],"process.":[62],"This":[63],"study":[64],"investigates":[65],"how":[66],"LLMs":[67,80,105,124],"can":[68,129],"minimize":[69],"effort":[70,132],"while":[71],"improving":[72],"accuracy.":[73,118],"In":[74],"Experiment":[75,98],"1,":[76],"performance":[78],"estimation":[83],"was":[84],"assessed,":[85],"showing":[86],"strong":[87],"accuracy":[88],"negative":[90],"despite":[92],"some":[93],"inconsistencies":[94],"with":[95,106],"human":[96],"annotations.":[97],"2":[99],"introduced":[100],"hybrid":[102],"approach":[103],"combining":[104],"deep":[107],"techniques":[109],"address":[111],"these":[112],"inconsistencies,":[113],"resulting":[114],"significantly":[116],"improved":[117],"These":[119],"findings":[120],"demonstrate":[121],"that":[122],"integrating":[123],"into":[125],"annotation":[127],"workflows":[128],"reduce":[130],"manual":[131],"enhance":[134],"accuracy,":[135],"offering":[136],"promising":[138],"pathway":[139],"applications":[143],"estimation.":[146]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-15T08:34:33.830935","created_date":"2025-10-10T00:00:00"}