{"id":"https://openalex.org/W4385194642","doi":"https://doi.org/10.1109/taffc.2023.3298405","title":"Text-Based Fine-Grained Emotion Prediction","display_name":"Text-Based Fine-Grained Emotion Prediction","publication_year":2023,"publication_date":"2023-07-24","ids":{"openalex":"https://openalex.org/W4385194642","doi":"https://doi.org/10.1109/taffc.2023.3298405"},"language":"en","primary_location":{"id":"doi:10.1109/taffc.2023.3298405","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taffc.2023.3298405","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"],"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/A5104385533","display_name":"Gargi Singh","orcid":"https://orcid.org/0009-0004-3884-8418"},"institutions":[{"id":"https://openalex.org/I94234084","display_name":"Indian Institute of Technology Kanpur","ror":"https://ror.org/05pjsgx75","country_code":"IN","type":"education","lineage":["https://openalex.org/I94234084"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Gargi Singh","raw_affiliation_strings":["CSE Department, Indian Institute of Technology Kanpur (IIT-K), Kanpur, Uttar Pradesh, India"],"affiliations":[{"raw_affiliation_string":"CSE Department, Indian Institute of Technology Kanpur (IIT-K), Kanpur, Uttar Pradesh, India","institution_ids":["https://openalex.org/I94234084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017497835","display_name":"Dhanajit Brahma","orcid":"https://orcid.org/0000-0003-4312-9341"},"institutions":[{"id":"https://openalex.org/I94234084","display_name":"Indian Institute of Technology Kanpur","ror":"https://ror.org/05pjsgx75","country_code":"IN","type":"education","lineage":["https://openalex.org/I94234084"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Dhanajit Brahma","raw_affiliation_strings":["CSE Department, Indian Institute of Technology Kanpur (IIT-K), Kanpur, Uttar Pradesh, India"],"affiliations":[{"raw_affiliation_string":"CSE Department, Indian Institute of Technology Kanpur (IIT-K), Kanpur, Uttar Pradesh, India","institution_ids":["https://openalex.org/I94234084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029651089","display_name":"Piyush Rai","orcid":"https://orcid.org/0000-0003-0660-8925"},"institutions":[{"id":"https://openalex.org/I94234084","display_name":"Indian Institute of Technology Kanpur","ror":"https://ror.org/05pjsgx75","country_code":"IN","type":"education","lineage":["https://openalex.org/I94234084"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Piyush Rai","raw_affiliation_strings":["CSE Department, Indian Institute of Technology Kanpur (IIT-K), Kanpur, Uttar Pradesh, India"],"affiliations":[{"raw_affiliation_string":"CSE Department, Indian Institute of Technology Kanpur (IIT-K), Kanpur, Uttar Pradesh, India","institution_ids":["https://openalex.org/I94234084"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076043215","display_name":"Ashutosh Modi","orcid":"https://orcid.org/0000-0002-0962-8350"},"institutions":[{"id":"https://openalex.org/I94234084","display_name":"Indian Institute of Technology Kanpur","ror":"https://ror.org/05pjsgx75","country_code":"IN","type":"education","lineage":["https://openalex.org/I94234084"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ashutosh Modi","raw_affiliation_strings":["CSE Department, Indian Institute of Technology Kanpur (IIT-K), Kanpur, Uttar Pradesh, India"],"affiliations":[{"raw_affiliation_string":"CSE Department, Indian Institute of Technology Kanpur (IIT-K), Kanpur, Uttar Pradesh, India","institution_ids":["https://openalex.org/I94234084"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5104385533"],"corresponding_institution_ids":["https://openalex.org/I94234084"],"apc_list":null,"apc_paid":null,"fwci":2.7804,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.92231695,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"15","issue":"2","first_page":"405","last_page":"416"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9973999857902527,"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":0.9937000274658203,"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/leverage","display_name":"Leverage (statistics)","score":0.7046223878860474},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6798808574676514},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6186485886573792},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.5949293375015259},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5438268184661865},{"id":"https://openalex.org/keywords/emotion-classification","display_name":"Emotion classification","score":0.511667013168335},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5007686614990234},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.49902772903442383},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.49900245666503906},{"id":"https://openalex.org/keywords/multi-task-learning","display_name":"Multi-task learning","score":0.4848717153072357},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47008633613586426},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4424275755882263},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.43526941537857056},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10807070136070251}],"concepts":[{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7046223878860474},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6798808574676514},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6186485886573792},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5949293375015259},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5438268184661865},{"id":"https://openalex.org/C206310091","wikidata":"https://www.wikidata.org/wiki/Q750859","display_name":"Emotion classification","level":2,"score":0.511667013168335},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5007686614990234},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.49902772903442383},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.49900245666503906},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.4848717153072357},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47008633613586426},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4424275755882263},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.43526941537857056},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10807070136070251},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/taffc.2023.3298405","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taffc.2023.3298405","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"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.75}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":58,"referenced_works":["https://openalex.org/W6094958","https://openalex.org/W39110104","https://openalex.org/W1546405367","https://openalex.org/W1566289585","https://openalex.org/W1966797434","https://openalex.org/W1972570464","https://openalex.org/W2032254851","https://openalex.org/W2041587709","https://openalex.org/W2066064791","https://openalex.org/W2082794029","https://openalex.org/W2118778378","https://openalex.org/W2134972645","https://openalex.org/W2149628368","https://openalex.org/W2182096631","https://openalex.org/W2339570520","https://openalex.org/W2544860892","https://openalex.org/W2599743206","https://openalex.org/W2806966100","https://openalex.org/W2892550322","https://openalex.org/W2900338016","https://openalex.org/W2905841571","https://openalex.org/W2920944394","https://openalex.org/W2929134750","https://openalex.org/W2936764189","https://openalex.org/W2950247511","https://openalex.org/W2963804400","https://openalex.org/W2965373594","https://openalex.org/W2970597249","https://openalex.org/W2974630751","https://openalex.org/W2996428491","https://openalex.org/W3005187732","https://openalex.org/W3012159372","https://openalex.org/W3034323190","https://openalex.org/W3095850336","https://openalex.org/W3116170960","https://openalex.org/W3128513378","https://openalex.org/W3212565998","https://openalex.org/W4200632936","https://openalex.org/W4287887917","https://openalex.org/W4296976275","https://openalex.org/W4385245566","https://openalex.org/W6604260396","https://openalex.org/W6719542159","https://openalex.org/W6742046398","https://openalex.org/W6742810063","https://openalex.org/W6751813305","https://openalex.org/W6752016773","https://openalex.org/W6753298111","https://openalex.org/W6755207826","https://openalex.org/W6763701032","https://openalex.org/W6766673545","https://openalex.org/W6767846310","https://openalex.org/W6768021236","https://openalex.org/W6773808816","https://openalex.org/W6779310007","https://openalex.org/W6787670637","https://openalex.org/W6791241415","https://openalex.org/W6846631807"],"related_works":["https://openalex.org/W2821676139","https://openalex.org/W4382138864","https://openalex.org/W3043695725","https://openalex.org/W4387770285","https://openalex.org/W3022215768","https://openalex.org/W3135975972","https://openalex.org/W3016888008","https://openalex.org/W4387183713","https://openalex.org/W4403518771","https://openalex.org/W2165698076"],"abstract_inverted_index":{"Text-based":[0],"emotion":[1,27,41,73,91,103,106,110,119,146,177,181],"prediction":[2,42,104,158,178],"is":[3],"an":[4,135],"important":[5],"task":[6,137,144],"in":[7,176],"the":[8,68,87,90,114,142,191,198],"field":[9],"of":[10,132,145],"affective":[11],"computing.":[12],"Most":[13],"prior":[14],"work":[15],"has":[16],"been":[17],"restricted":[18],"to":[19,23,58,85],"predicting":[20],"emotions":[21,133],"corresponding":[22],"a":[24,56,83,97,125],"few":[25],"high-level":[26],"classes.":[28],"This":[29],"paper":[30],"explores":[31],"and":[32,75,93,155,185],"experiments":[33,196],"with":[34,76,179],"various":[35],"techniques":[36],"for":[37,100,117,169],"fine-grained":[38,102,118],"(27":[39],"classes)":[40],"<sup":[43],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[44],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">\u2020</sup>":[45],"which":[46],"appeared":[47],"at":[48],"ACII":[49],"2021.":[50],"In":[51],"particular,":[52],"(1)":[53],"we":[54,66,81,95],"present":[55,82],"method":[57,84],"incorporate":[59],"multiple":[60],"annotations":[61],"from":[62],"different":[63],"raters,":[64],"(2)":[65],"analyze":[67],"model's":[69,199],"performance":[70],"on":[71,141,172,193],"fused":[72],"classes":[74],"sub-sampled":[77],"training":[78],"data,":[79],"(3)":[80],"leverage":[86],"correlations":[88],"among":[89],"categories,":[92],"(4)":[94],"propose":[96],"new":[98],"framework":[99,128],"text-based":[101],"through":[105],"definition":[107,157],"modeling.":[108],"The":[109,122,187],"definition-based":[111],"model":[112,149,165],"outperforms":[113],"existing":[115],"state-of-the-art":[116],"dataset":[120],"GoEmotions.":[121],"approach":[123],"involves":[124],"multi-task":[126],"learning":[127,171,195],"that":[129,162],"models":[130,189],"definitions":[131,150],"as":[134],"auxiliary":[136],"while":[138],"being":[139],"trained":[140,164],"primary":[143],"prediction.":[147],"We":[148,160],"using":[151],"masked":[152],"language":[153],"modeling":[154],"class":[156],"tasks.":[159],"show":[161],"this":[163],"can":[166],"be":[167],"used":[168],"transfer":[170,194],"other":[173],"benchmark":[174],"datasets":[175],"varying":[180],"label":[182],"sets,":[183],"domains,":[184],"sizes.":[186],"proposed":[188],"outperform":[190],"baselines":[192],"demonstrating":[197],"generalization":[200],"capability.":[201]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":7}],"updated_date":"2026-03-31T07:56:22.981413","created_date":"2025-10-10T00:00:00"}
