{"id":"https://openalex.org/W4411799176","doi":"https://doi.org/10.1109/taffc.2025.3584775","title":"Rethinking Emotion Annotations in the Era of Large Language Models","display_name":"Rethinking Emotion Annotations in the Era of Large Language Models","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4411799176","doi":"https://doi.org/10.1109/taffc.2025.3584775","pmid":"https://pubmed.ncbi.nlm.nih.gov/41584426"},"language":"en","primary_location":{"id":"doi:10.1109/taffc.2025.3584775","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taffc.2025.3584775","pdf_url":null,"source":{"id":"https://openalex.org/S104780363","display_name":"IEEE Transactions on Affective Computing","issn_l":"1949-3045","issn":["1949-3045","2371-9850"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Affective Computing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12826563/","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5011197815","display_name":"Minxue Niu","orcid":"https://orcid.org/0009-0007-8266-9152"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Minxue Niu","raw_affiliation_strings":["University of Michigan, Ann Arbor, MI, USA","University of Michigan, Ann Arbor, USA"],"affiliations":[{"raw_affiliation_string":"University of Michigan, Ann Arbor, MI, USA","institution_ids":["https://openalex.org/I27837315"]},{"raw_affiliation_string":"University of Michigan, Ann Arbor, USA","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106912466","display_name":"Yara El-Tawil","orcid":null},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yara El-Tawil","raw_affiliation_strings":["University of Michigan, Ann Arbor, MI, USA","University of Michigan, Ann Arbor, USA"],"affiliations":[{"raw_affiliation_string":"University of Michigan, Ann Arbor, MI, USA","institution_ids":["https://openalex.org/I27837315"]},{"raw_affiliation_string":"University of Michigan, Ann Arbor, USA","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035651773","display_name":"Amrit Romana","orcid":"https://orcid.org/0009-0005-2360-0732"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Amrit Romana","raw_affiliation_strings":["University of Michigan, Ann Arbor, MI, USA","University of Michigan, Ann Arbor, USA"],"affiliations":[{"raw_affiliation_string":"University of Michigan, Ann Arbor, MI, USA","institution_ids":["https://openalex.org/I27837315"]},{"raw_affiliation_string":"University of Michigan, Ann Arbor, USA","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003136334","display_name":"Emily Mower Provost","orcid":"https://orcid.org/0000-0003-1870-6063"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Emily Mower Provost","raw_affiliation_strings":["University of Michigan, Ann Arbor, MI, USA","University of Michigan, Ann Arbor, USA"],"affiliations":[{"raw_affiliation_string":"University of Michigan, Ann Arbor, MI, USA","institution_ids":["https://openalex.org/I27837315"]},{"raw_affiliation_string":"University of Michigan, Ann Arbor, USA","institution_ids":["https://openalex.org/I27837315"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5011197815"],"corresponding_institution_ids":["https://openalex.org/I27837315"],"apc_list":null,"apc_paid":null,"fwci":5.0294,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.9501371,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"16","issue":"4","first_page":"2668","last_page":"2679"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9693999886512756,"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/T10028","display_name":"Topic Modeling","score":0.9693999886512756,"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":0.9257000088691711,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9247999787330627,"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":0.4655248820781708},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4478788673877716},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.4371834993362427},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.40195900201797485},{"id":"https://openalex.org/keywords/cognitive-science","display_name":"Cognitive science","score":0.3984795808792114},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35880622267723083},{"id":"https://openalex.org/keywords/cognitive-psychology","display_name":"Cognitive psychology","score":0.3511689603328705},{"id":"https://openalex.org/keywords/philosophy","display_name":"Philosophy","score":0.1707872450351715}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4655248820781708},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4478788673877716},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.4371834993362427},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.40195900201797485},{"id":"https://openalex.org/C188147891","wikidata":"https://www.wikidata.org/wiki/Q147638","display_name":"Cognitive science","level":1,"score":0.3984795808792114},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35880622267723083},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.3511689603328705},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.1707872450351715}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/taffc.2025.3584775","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taffc.2025.3584775","pdf_url":null,"source":{"id":"https://openalex.org/S104780363","display_name":"IEEE Transactions on Affective Computing","issn_l":"1949-3045","issn":["1949-3045","2371-9850"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Affective Computing","raw_type":"journal-article"},{"id":"pmid:41584426","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41584426","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on affective computing","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:12826563","is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12826563/","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Trans Affect Comput","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:pubmedcentral.nih.gov:12826563","is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12826563/","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Trans Affect Comput","raw_type":"Text"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.46000000834465027}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":64,"referenced_works":["https://openalex.org/W207824403","https://openalex.org/W1522611117","https://openalex.org/W1966797434","https://openalex.org/W1988733743","https://openalex.org/W2007450092","https://openalex.org/W2058787788","https://openalex.org/W2087356051","https://openalex.org/W2089041530","https://openalex.org/W2117645142","https://openalex.org/W2123402141","https://openalex.org/W2145598468","https://openalex.org/W2149628368","https://openalex.org/W2151905266","https://openalex.org/W2404535984","https://openalex.org/W2525412388","https://openalex.org/W2550557083","https://openalex.org/W2585292421","https://openalex.org/W2741036097","https://openalex.org/W2763103160","https://openalex.org/W2772749911","https://openalex.org/W2802909724","https://openalex.org/W2805744755","https://openalex.org/W2896277673","https://openalex.org/W2896457183","https://openalex.org/W2914073361","https://openalex.org/W2924124898","https://openalex.org/W2960022945","https://openalex.org/W2963162726","https://openalex.org/W2968055463","https://openalex.org/W2971307358","https://openalex.org/W3034323190","https://openalex.org/W3082689825","https://openalex.org/W3133702157","https://openalex.org/W3185341429","https://openalex.org/W3206765301","https://openalex.org/W4210910835","https://openalex.org/W4220887861","https://openalex.org/W4294982692","https://openalex.org/W4318919287","https://openalex.org/W4384662964","https://openalex.org/W4385571411","https://openalex.org/W4385572910","https://openalex.org/W4388708748","https://openalex.org/W4389519042","https://openalex.org/W4389519841","https://openalex.org/W4389917421","https://openalex.org/W4389917881","https://openalex.org/W4390874371","https://openalex.org/W4391021627","https://openalex.org/W4392903618","https://openalex.org/W4398150831","https://openalex.org/W4399154371","https://openalex.org/W4401042286","https://openalex.org/W4401863339","https://openalex.org/W4402111569","https://openalex.org/W4402671727","https://openalex.org/W4402671909","https://openalex.org/W4402715027","https://openalex.org/W4403246846","https://openalex.org/W4403486837","https://openalex.org/W4404783774","https://openalex.org/W4406524040","https://openalex.org/W4408347320","https://openalex.org/W4409762247"],"related_works":["https://openalex.org/W3188962172","https://openalex.org/W2772917594","https://openalex.org/W4312825515","https://openalex.org/W4306742369","https://openalex.org/W4303457083","https://openalex.org/W2131146434","https://openalex.org/W2951359407","https://openalex.org/W4376623224","https://openalex.org/W4387849428","https://openalex.org/W3204019825"],"abstract_inverted_index":{"Modern":[0],"affective":[1],"computing":[2],"systems":[3],"rely":[4],"heavily":[5],"on":[6,49,79],"datasets":[7],"with":[8],"human-annotated":[9],"emotion":[10,71,126,153,184],"labels":[11,108],"for":[12,60,182],"both":[13],"training":[14],"and":[15,28,124,169,175,187],"evaluation.":[16],"However,":[17],"human":[18,94,107,123,132,143,167,199],"annotations":[19],"are":[20],"expensive":[21],"to":[22,25,30,159,197],"obtain,":[23],"sensitive":[24],"study":[26],"design,":[27],"difficult":[29],"quality":[31],"control,":[32],"because":[33],"of":[34,38,70,76,131,149,166,191],"the":[35,68,74,111,116,129,164,189],"subjective":[36],"nature":[37],"emotions.":[39],"Meanwhile,":[40],"Large":[41],"Language":[42,52],"Models":[43],"(LLMs)":[44],"have":[45],"shown":[46],"remarkable":[47],"performance":[48,174],"many":[50],"Natural":[51],"Understanding":[53],"tasks,":[54],"emerging":[55],"as":[56,81,110,193],"a":[57,82,93,98,194],"promising":[58,195],"tool":[59,196],"text":[61],"annotation.":[62,200],"In":[63,85],"this":[64],"work,":[65,104],"we":[66,119,145],"analyze":[67],"complexities":[69],"annotation":[72,135,154],"in":[73,92,105,134],"context":[75],"LLMs,":[77],"focusing":[78],"GPT-4":[80,88,125,151],"leading":[83],"model.":[84],"our":[86,178],"experiments,":[87],"achieves":[89],"high":[90],"ratings":[91],"evaluation":[95],"study,":[96],"painting":[97],"more":[99],"positive":[100],"picture":[101],"than":[102],"previous":[103],"which":[106],"served":[109],"only":[112],"ground":[113],"truth.":[114],"On":[115],"other":[117],"hand,":[118],"observe":[120],"differences":[121],"between":[122],"perception,":[127],"underscoring":[128],"importance":[130],"input":[133],"studies.":[136],"To":[137],"harness":[138],"GPT-4's":[139],"strength":[140],"while":[141],"preserving":[142],"perspective,":[144],"explore":[146],"two":[147],"ways":[148],"integrating":[150],"into":[152],"pipelines,":[155],"showing":[156],"its":[157],"potential":[158],"flag":[160],"low-quality":[161],"labels,":[162],"reduce":[163],"workload":[165],"annotators,":[168],"improve":[170],"downstream":[171],"model":[172],"learning":[173],"efficiency.":[176],"Together,":[177],"findings":[179],"highlight":[180],"opportunities":[181],"new":[183],"labeling":[185],"practices":[186],"suggest":[188],"use":[190],"LLMs":[192],"aid":[198]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-27T14:29:43.386196","created_date":"2025-10-10T00:00:00"}
