{"id":"https://openalex.org/W2955429306","doi":"https://doi.org/10.18653/v1/s19-2005","title":"SemEval-2019 Task 3: EmoContext Contextual Emotion Detection in Text","display_name":"SemEval-2019 Task 3: EmoContext Contextual Emotion Detection in Text","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2955429306","doi":"https://doi.org/10.18653/v1/s19-2005","mag":"2955429306"},"language":"en","primary_location":{"id":"doi:10.18653/v1/s19-2005","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s19-2005","pdf_url":"https://www.aclweb.org/anthology/S19-2005.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 13th International Workshop on Semantic Evaluation","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/S19-2005.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5044973780","display_name":"Ankush Chatterjee","orcid":null},"institutions":[{"id":"https://openalex.org/I4210162141","display_name":"Microsoft (India)","ror":"https://ror.org/04ww0w091","country_code":"IN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210162141"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ankush Chatterjee","raw_affiliation_strings":["Microsoft, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft, India","institution_ids":["https://openalex.org/I4210162141"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033118922","display_name":"Kedhar Nath Narahari","orcid":null},"institutions":[{"id":"https://openalex.org/I4210162141","display_name":"Microsoft (India)","ror":"https://ror.org/04ww0w091","country_code":"IN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210162141"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Kedhar Nath Narahari","raw_affiliation_strings":["Microsoft, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft, India","institution_ids":["https://openalex.org/I4210162141"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108813961","display_name":"Meghana Joshi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210162141","display_name":"Microsoft (India)","ror":"https://ror.org/04ww0w091","country_code":"IN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210162141"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Meghana Joshi","raw_affiliation_strings":["Microsoft, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft, India","institution_ids":["https://openalex.org/I4210162141"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064683413","display_name":"Puneet Agrawal","orcid":"https://orcid.org/0000-0002-5745-7330"},"institutions":[{"id":"https://openalex.org/I4210162141","display_name":"Microsoft (India)","ror":"https://ror.org/04ww0w091","country_code":"IN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210162141"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Puneet Agrawal","raw_affiliation_strings":["Microsoft, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft, India","institution_ids":["https://openalex.org/I4210162141"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":24.5832,"has_fulltext":true,"cited_by_count":288,"citation_normalized_percentile":{"value":0.99601822,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"39","last_page":"48"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9998999834060669,"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":0.9983999729156494,"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/utterance","display_name":"Utterance","score":0.7900420427322388},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7402132153511047},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.7068054676055908},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6601377129554749},{"id":"https://openalex.org/keywords/semeval","display_name":"SemEval","score":0.6564587354660034},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6467009782791138},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.6272096633911133},{"id":"https://openalex.org/keywords/ambiguity","display_name":"Ambiguity","score":0.6180035471916199},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5558665990829468},{"id":"https://openalex.org/keywords/emotion-detection","display_name":"Emotion detection","score":0.5353078842163086},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4903149902820587},{"id":"https://openalex.org/keywords/emotion-classification","display_name":"Emotion classification","score":0.46603530645370483},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.41111594438552856},{"id":"https://openalex.org/keywords/emotion-recognition","display_name":"Emotion recognition","score":0.28599315881729126}],"concepts":[{"id":"https://openalex.org/C2775852435","wikidata":"https://www.wikidata.org/wiki/Q258403","display_name":"Utterance","level":2,"score":0.7900420427322388},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7402132153511047},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7068054676055908},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6601377129554749},{"id":"https://openalex.org/C44572571","wikidata":"https://www.wikidata.org/wiki/Q7448970","display_name":"SemEval","level":3,"score":0.6564587354660034},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6467009782791138},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.6272096633911133},{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.6180035471916199},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5558665990829468},{"id":"https://openalex.org/C2988148770","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion detection","level":3,"score":0.5353078842163086},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4903149902820587},{"id":"https://openalex.org/C206310091","wikidata":"https://www.wikidata.org/wiki/Q750859","display_name":"Emotion classification","level":2,"score":0.46603530645370483},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.41111594438552856},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.28599315881729126},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/s19-2005","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s19-2005","pdf_url":"https://www.aclweb.org/anthology/S19-2005.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 13th International Workshop on Semantic Evaluation","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/s19-2005","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s19-2005","pdf_url":"https://www.aclweb.org/anthology/S19-2005.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 13th International Workshop on Semantic Evaluation","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.699999988079071,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2955429306.pdf","grobid_xml":"https://content.openalex.org/works/W2955429306.grobid-xml"},"referenced_works_count":51,"referenced_works":["https://openalex.org/W17944974","https://openalex.org/W37461795","https://openalex.org/W50950926","https://openalex.org/W104683736","https://openalex.org/W1832693441","https://openalex.org/W1924770834","https://openalex.org/W1966797434","https://openalex.org/W1969386661","https://openalex.org/W1971028513","https://openalex.org/W1971222444","https://openalex.org/W2064675550","https://openalex.org/W2079521622","https://openalex.org/W2112251034","https://openalex.org/W2131774270","https://openalex.org/W2136879928","https://openalex.org/W2141403362","https://openalex.org/W2163605009","https://openalex.org/W2168493061","https://openalex.org/W2168872737","https://openalex.org/W2217829525","https://openalex.org/W2250539671","https://openalex.org/W2295598076","https://openalex.org/W2321563513","https://openalex.org/W2404480901","https://openalex.org/W2466545435","https://openalex.org/W2556247010","https://openalex.org/W2606292552","https://openalex.org/W2732463225","https://openalex.org/W2738554243","https://openalex.org/W2741447225","https://openalex.org/W2748543394","https://openalex.org/W2749002090","https://openalex.org/W2750747353","https://openalex.org/W2756723094","https://openalex.org/W2768348081","https://openalex.org/W2794557536","https://openalex.org/W2896457183","https://openalex.org/W2898536220","https://openalex.org/W2905807898","https://openalex.org/W2962739339","https://openalex.org/W2962830617","https://openalex.org/W2963026768","https://openalex.org/W2963291843","https://openalex.org/W2963341956","https://openalex.org/W2963712766","https://openalex.org/W3102476541","https://openalex.org/W3106003309","https://openalex.org/W3122775348","https://openalex.org/W4234180827","https://openalex.org/W4234200325","https://openalex.org/W4243716403"],"related_works":["https://openalex.org/W2956016035","https://openalex.org/W2955767635","https://openalex.org/W2955722679","https://openalex.org/W4281557318","https://openalex.org/W4308351423","https://openalex.org/W2314410016","https://openalex.org/W2953739332","https://openalex.org/W2955000657","https://openalex.org/W2165412197","https://openalex.org/W104683736"],"abstract_inverted_index":{"In":[0,73],"this":[1,74,117,174],"paper,":[2],"we":[3,42],"present":[4],"the":[5,54,61,71,90,95,99,114,164,186,201,208,219,222,226,231,234],"SemEval-2019":[6],"Task":[7],"3":[8],"-EmoContext:":[9],"Contextual":[10],"Emotion":[11],"Detection":[12],"in":[13,25,68,116],"Text.":[14],"Lack":[15],"of":[16,63,70,88,98,144,168,197,212,218],"facial":[17],"expressions":[18],"and":[19,53,110,130,147,153,157,185,216,230],"voice":[20],"modulations":[21],"make":[22],"detecting":[23],"emotions":[24],"text":[26,40],"a":[27,48,77,125],"challenging":[28],"problem.":[29],"For":[30],"instance,":[31],"as":[32,47],"humans,":[33],"on":[34,181],"reading":[35],"\"Why":[36],"don't":[37],"you":[38],"ever":[39],"me!\"":[41],"can":[43,65],"either":[44],"interpret":[45],"it":[46],"sad":[49],"or":[50],"angry":[51],"emotion":[52,97,105,133,228,236],"same":[55],"ambiguity":[56],"exists":[57],"for":[58,132,225,233],"machines.":[59],"However,":[60],"context":[62],"dialogue":[64,79],"prove":[66],"helpful":[67],"detection":[69],"emotion.":[72],"task,":[75,118],"given":[76],"textual":[78,119],"i.e.":[80],"an":[81],"utterance":[82,100],"along":[83],"with":[84,124],"two":[85,148],"previous":[86],"turns":[87],"context,":[89],"goal":[91],"was":[92,179,207],"to":[93,163,173,200],"infer":[94],"underlying":[96],"by":[101],"choosing":[102],"from":[103,121],"four":[104],"classes":[106,134],"-Happy,":[107],"Sad,":[108],"Angry":[109],"Others.":[111],"To":[112],"facilitate":[113],"participation":[115],"dialogues":[120,159],"user":[122],"interaction":[123],"conversational":[126],"agent":[127],"were":[128,161],"taken":[129],"annotated":[131],"after":[135],"several":[136],"data":[137,142,150,183],"processing":[138],"steps.":[139],"A":[140,166],"training":[141],"set":[143],"30160":[145],"dialogues,":[146],"evaluation":[149],"sets,":[151],"Test1":[152],"Test2,":[154],"containing":[155],"2755":[156],"5509":[158],"respectively":[160],"released":[162],"participants.":[165],"total":[167],"311":[169],"teams":[170],"made":[171],"submissions":[172],"task.":[175],"The":[176],"final":[177],"leader-board":[178],"evaluated":[180],"Test2":[182],"set,":[184],"highest":[187],"ranked":[188],"submission":[189],"achieved":[190],"79.59":[191],"micro-averaged":[192],"F1":[193],"score.":[194],"Our":[195],"analysis":[196],"systems":[198,220],"submitted":[199],"task":[202],"indicate":[203],"that":[204],"Bi-directional":[205],"LSTM":[206],"most":[209,217],"common":[210],"choice":[211],"neural":[213],"architecture":[214],"used,":[215],"had":[221],"best":[223],"performance":[224],"Sad":[227],"class,":[229],"worst":[232],"Happy":[235],"class.":[237]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":25},{"year":2024,"cited_by_count":38},{"year":2023,"cited_by_count":50},{"year":2022,"cited_by_count":23},{"year":2021,"cited_by_count":48},{"year":2020,"cited_by_count":36},{"year":2019,"cited_by_count":63}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
