{"id":"https://openalex.org/W4397035441","doi":"https://doi.org/10.47363/jbber/2024(2)118","title":"Advancing Sentiment Analysis Through Emotionally-Agnostic Text Mining in Large Language Models (LLMS)","display_name":"Advancing Sentiment Analysis Through Emotionally-Agnostic Text Mining in Large Language Models (LLMS)","publication_year":2024,"publication_date":"2024-05-18","ids":{"openalex":"https://openalex.org/W4397035441","doi":"https://doi.org/10.47363/jbber/2024(2)118"},"language":"en","primary_location":{"id":"doi:10.47363/jbber/2024(2)118","doi":"https://doi.org/10.47363/jbber/2024(2)118","is_oa":false,"landing_page_url":"https://doi.org/10.47363/jbber/2024(2)118","pdf_url":null,"source":{"id":"https://openalex.org/S4387289342","display_name":"Journal of Biosensors and Bioelectronics Research","issn_l":"2976-7466","issn":["2976-7466"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Biosensors and Bioelectronics Research","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/A5052787141","display_name":"James Hutson","orcid":"https://orcid.org/0000-0002-0578-6052","observed_orcids":["https://orcid.org/0000-0002-0578-6052"]},"institutions":[{"id":"https://openalex.org/I98865867","display_name":"Lindenwood University","ror":"https://ror.org/01qf95793","country_code":"US","type":"education","lineage":["https://openalex.org/I98865867"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"James Hutson","raw_affiliation_strings":["Department Head of Art History and Visual Culture, College of Arts and Humanities, Lindenwood University, Saint Charles, MO, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department Head of Art History and Visual Culture, College of Arts and Humanities, Lindenwood University, Saint Charles, MO, USA","institution_ids":["https://openalex.org/I98865867"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016357418","display_name":"Jeremiah Ratican","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I98865867","display_name":"Lindenwood University","ror":"https://ror.org/01qf95793","country_code":"US","type":"education","lineage":["https://openalex.org/I98865867"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jeremiah Ratican","raw_affiliation_strings":["Program Coordinator of Game Design, College of Arts and Humanities, Lindenwood University, Saint Charles, MO, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Program Coordinator of Game Design, College of Arts and Humanities, Lindenwood University, Saint Charles, MO, USA","institution_ids":["https://openalex.org/I98865867"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I98865867"],"apc_list":null,"apc_paid":null,"fwci":1.4054,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.82567511,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":99},"biblio":{"volume":"2","issue":"3","first_page":"1","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":1.0,"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":1.0,"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":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"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.0,"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":0.9919999837875366},{"id":"https://openalex.org/keywords/large-language-models","display_name":"large language models","score":0.8809999823570251},{"id":"https://openalex.org/keywords/emotion-recognition","display_name":"emotion recognition","score":0.8009999990463257},{"id":"https://openalex.org/keywords/physiological-cues","display_name":"physiological cues","score":0.5590000152587891},{"id":"https://openalex.org/keywords/character-ai","display_name":"Character.AI","score":0.6480000019073486},{"id":"https://openalex.org/keywords/short-term-memory","display_name":"short-term memory","score":0.7129999995231628},{"id":"https://openalex.org/keywords/recommender-systems","display_name":"recommender systems","score":0.5619999766349792}],"concepts":[{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.7986828088760376},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.572762668132782},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.527818500995636},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.4494119882583618},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.4333769381046295},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.429470032453537},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40092939138412476},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.3496440052986145},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.34076666831970215}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.47363/jbber/2024(2)118","doi":"https://doi.org/10.47363/jbber/2024(2)118","is_oa":false,"landing_page_url":"https://doi.org/10.47363/jbber/2024(2)118","pdf_url":null,"source":{"id":"https://openalex.org/S4387289342","display_name":"Journal of Biosensors and Bioelectronics Research","issn_l":"2976-7466","issn":["2976-7466"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Biosensors and Bioelectronics Research","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":83,"referenced_works":["https://openalex.org/W42507093","https://openalex.org/W102542129","https://openalex.org/W258136322","https://openalex.org/W641739510","https://openalex.org/W1484665644","https://openalex.org/W1831214525","https://openalex.org/W1965479312","https://openalex.org/W1974256076","https://openalex.org/W1984243459","https://openalex.org/W1990623057","https://openalex.org/W1998260720","https://openalex.org/W2011881150","https://openalex.org/W2015079474","https://openalex.org/W2035462632","https://openalex.org/W2057664615","https://openalex.org/W2066838006","https://openalex.org/W2083613342","https://openalex.org/W2089143194","https://openalex.org/W2100730338","https://openalex.org/W2148937976","https://openalex.org/W2252686044","https://openalex.org/W2578742563","https://openalex.org/W2598636128","https://openalex.org/W2610596325","https://openalex.org/W2640252219","https://openalex.org/W2802125196","https://openalex.org/W2900008031","https://openalex.org/W2908092214","https://openalex.org/W2914591547","https://openalex.org/W2926888228","https://openalex.org/W2934302500","https://openalex.org/W2947452701","https://openalex.org/W2965472222","https://openalex.org/W2992107592","https://openalex.org/W2995050449","https://openalex.org/W3004032521","https://openalex.org/W3038047461","https://openalex.org/W3103255514","https://openalex.org/W3119092446","https://openalex.org/W3119341943","https://openalex.org/W3119410748","https://openalex.org/W3123099576","https://openalex.org/W3124143793","https://openalex.org/W3124815229","https://openalex.org/W3143363932","https://openalex.org/W3158914885","https://openalex.org/W3159655937","https://openalex.org/W3200991626","https://openalex.org/W4200546216","https://openalex.org/W4200587778","https://openalex.org/W4206544990","https://openalex.org/W4211112912","https://openalex.org/W4220944085","https://openalex.org/W4220963437","https://openalex.org/W4221106847","https://openalex.org/W4236415216","https://openalex.org/W4284966012","https://openalex.org/W4291152088","https://openalex.org/W4294437784","https://openalex.org/W4316589236","https://openalex.org/W4319317626","https://openalex.org/W4319439681","https://openalex.org/W4319599375","https://openalex.org/W4319835296","https://openalex.org/W4324135233","https://openalex.org/W4328024808","https://openalex.org/W4353100796","https://openalex.org/W4362655490","https://openalex.org/W4365512576","https://openalex.org/W4366083396","https://openalex.org/W4367175999","https://openalex.org/W4378474327","https://openalex.org/W4379410101","https://openalex.org/W4383113604","https://openalex.org/W4385015470","https://openalex.org/W4385625465","https://openalex.org/W4385963839","https://openalex.org/W4386119080","https://openalex.org/W4387665615","https://openalex.org/W4387835442","https://openalex.org/W4387905019","https://openalex.org/W4392956693","https://openalex.org/W4406800520"],"related_works":["https://openalex.org/W4403751239","https://openalex.org/W4411172594","https://openalex.org/W4407847484","https://openalex.org/W4416178454","https://openalex.org/W7130555830","https://openalex.org/W7088184888","https://openalex.org/W4403421521","https://openalex.org/W7214117685","https://openalex.org/W4416126130","https://openalex.org/W6911778411"],"abstract_inverted_index":{"The":[0,59,146],"conventional":[1],"methodology":[2],"for":[3,84,101,128,187,228],"sentiment":[4,39,64,87,121,160,212,219],"analysis":[5,40,65,88,161,213],"within":[6,122,202,222],"large":[7],"language":[8],"models":[9],"(LLMs)":[10],"has":[11],"predominantly":[12],"drawn":[13],"upon":[14],"human":[15,56,243],"emotional":[16,205,235,271],"frameworks,":[17],"incorporating":[18],"physiological":[19,57,93,244],"cues":[20],"that":[21,90,209],"are":[22],"inherently":[23],"absent":[24],"in":[25,41,250,267],"text-only":[26],"communication.":[27],"This":[28,78,238],"research":[29,147],"proposes":[30],"a":[31,81,117,133,149,203,229,247],"paradigm":[32],"shift":[33],"towards":[34],"an":[35,85],"emotionallyagnostic":[36],"approach":[37,113,214],"to":[38,62,67,111,163,168,195,199,258],"LLMs,":[42,183],"which":[43,125],"concentrates":[44],"on":[45],"purely":[46],"textual":[47],"expressions":[48],"of":[49,55,108,120,135,182,242,261],"sentiment,":[50],"circumventing":[51],"the":[52,97,154,174,178,185,218,259],"confounding":[53],"effects":[54],"responses.":[58],"aim":[60],"is":[61,114,126,273],"refine":[63],"algorithms":[66],"discern":[68],"and":[69,142,167,192,197,232,256],"generate":[70],"emotionally":[71],"congruent":[72],"responses":[73],"strictly":[74],"from":[75],"text-based":[76],"cues.":[77],"study":[79],"presents":[80],"comprehensive":[82],"framework":[83],"emotionally-agnostic":[86,211],"model":[89,157],"systematically":[91],"excludes":[92],"indicators":[94],"whilst":[95],"maintaining":[96],"analytical":[98,265],"depth":[99],"required":[100],"accurate":[102],"emotion":[103],"detection.":[104],"A":[105],"novel":[106],"suite":[107],"metrics":[109],"tailored":[110],"this":[112,210],"developed,":[115],"facilitating":[116],"nuanced":[118],"interpretation":[119],"text":[123,136,251],"data,":[124],"paramount":[127],"enhancing":[129],"user":[130,200],"interaction":[131],"across":[132],"spectrum":[134],"mining":[137],"applications,":[138],"including":[139],"recommendation":[140],"systems":[141],"interactive":[143],"AI":[144,189],"characters.":[145],"undertakes":[148],"critical":[150],"comparative":[151],"analysis,":[152],"juxtaposing":[153],"newly":[155],"proposed":[156],"with":[158],"traditional":[159],"techniques,":[162],"evaluate":[164],"efficacy":[165],"enhancements":[166],"substantiate":[169],"its":[170],"application":[171],"potential.":[172],"Further,":[173],"investigation":[175],"delves":[176],"into":[177],"short-term":[179],"memory":[180],"capabilities":[181],"exploring":[184],"implications":[186],"character":[188],"roleplaying":[190],"interfaces":[191],"their":[193],"ability":[194],"recall":[196],"respond":[198],"input":[201],"text-driven":[204],"framework.":[206],"Findings":[207],"indicate":[208],"not":[215],"only":[216],"simplifies":[217],"assessment":[220],"process":[221],"LLMs":[223,262],"but":[224],"also":[225],"opens":[226],"avenues":[227],"more":[230],"precise":[231],"contextually":[233],"appropriate":[234],"response":[236],"generation.":[237],"abstracted":[239],"model,":[240],"devoid":[241],"constraints,":[245],"represents":[246],"significant":[248],"advancement":[249],"mining,":[252],"fostering":[253],"improved":[254],"interactions":[255],"contributing":[257],"evolution":[260],"as":[263],"adept":[264],"tools":[266],"various":[268],"domains":[269],"where":[270],"intelligence":[272],"crucial.":[274]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2024-05-19T00:00:00"}