{"id":"https://openalex.org/W2168980558","doi":"https://doi.org/10.1109/acii.2009.5349598","title":"Sentence level emotion tagging","display_name":"Sentence level emotion tagging","publication_year":2009,"publication_date":"2009-09-01","ids":{"openalex":"https://openalex.org/W2168980558","doi":"https://doi.org/10.1109/acii.2009.5349598","mag":"2168980558"},"language":"en","primary_location":{"id":"doi:10.1109/acii.2009.5349598","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acii.2009.5349598","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops","raw_type":"proceedings-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/A5052810907","display_name":"Dipankar Das","orcid":"https://orcid.org/0000-0002-8110-9344"},"institutions":[{"id":"https://openalex.org/I170979836","display_name":"Jadavpur University","ror":"https://ror.org/02af4h012","country_code":"IN","type":"education","lineage":["https://openalex.org/I170979836"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Dipankar Das","raw_affiliation_strings":["Department of Computer Science & Engineering, Jadavpur University, Kolkata, India","Jadavpur University, Department of Computer Science and Engineering, Kolkata 700032, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, Jadavpur University, Kolkata, India","institution_ids":["https://openalex.org/I170979836"]},{"raw_affiliation_string":"Jadavpur University, Department of Computer Science and Engineering, Kolkata 700032, India","institution_ids":["https://openalex.org/I170979836"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006218020","display_name":"Sivaji Bandyopadhyay","orcid":"https://orcid.org/0000-0003-2607-1774"},"institutions":[{"id":"https://openalex.org/I170979836","display_name":"Jadavpur University","ror":"https://ror.org/02af4h012","country_code":"IN","type":"education","lineage":["https://openalex.org/I170979836"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sivaji Bandyopadhyay","raw_affiliation_strings":["Department of Computer Science & Engineering, Jadavpur University, Kolkata, India","Jadavpur University, Department of Computer Science and Engineering, Kolkata 700032, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, Jadavpur University, Kolkata, India","institution_ids":["https://openalex.org/I170979836"]},{"raw_affiliation_string":"Jadavpur University, Department of Computer Science and Engineering, Kolkata 700032, India","institution_ids":["https://openalex.org/I170979836"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5052810907"],"corresponding_institution_ids":["https://openalex.org/I170979836"],"apc_list":null,"apc_paid":null,"fwci":2.6171,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.91179569,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"39","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9998999834060669,"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/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/T11644","display_name":"Spam and Phishing Detection","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9958000183105469,"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":0.7305831909179688},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6922091245651245},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.6816613674163818},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6661702394485474},{"id":"https://openalex.org/keywords/wordnet","display_name":"WordNet","score":0.5714940428733826},{"id":"https://openalex.org/keywords/valence","display_name":"Valence (chemistry)","score":0.5575724244117737},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.5132424831390381},{"id":"https://openalex.org/keywords/anger","display_name":"Anger","score":0.5102713108062744},{"id":"https://openalex.org/keywords/emotion-classification","display_name":"Emotion classification","score":0.47080859541893005},{"id":"https://openalex.org/keywords/surprise","display_name":"Surprise","score":0.4698936939239502},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.46228814125061035},{"id":"https://openalex.org/keywords/disgust","display_name":"Disgust","score":0.44556087255477905},{"id":"https://openalex.org/keywords/semeval","display_name":"SemEval","score":0.43127843737602234},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.428725928068161},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.20608681440353394},{"id":"https://openalex.org/keywords/communication","display_name":"Communication","score":0.10961788892745972}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7305831909179688},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6922091245651245},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.6816613674163818},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6661702394485474},{"id":"https://openalex.org/C157659113","wikidata":"https://www.wikidata.org/wiki/Q533822","display_name":"WordNet","level":2,"score":0.5714940428733826},{"id":"https://openalex.org/C168900304","wikidata":"https://www.wikidata.org/wiki/Q171407","display_name":"Valence (chemistry)","level":2,"score":0.5575724244117737},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.5132424831390381},{"id":"https://openalex.org/C2779302386","wikidata":"https://www.wikidata.org/wiki/Q79871","display_name":"Anger","level":2,"score":0.5102713108062744},{"id":"https://openalex.org/C206310091","wikidata":"https://www.wikidata.org/wiki/Q750859","display_name":"Emotion classification","level":2,"score":0.47080859541893005},{"id":"https://openalex.org/C2780343955","wikidata":"https://www.wikidata.org/wiki/Q333173","display_name":"Surprise","level":2,"score":0.4698936939239502},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.46228814125061035},{"id":"https://openalex.org/C2777375102","wikidata":"https://www.wikidata.org/wiki/Q208351","display_name":"Disgust","level":3,"score":0.44556087255477905},{"id":"https://openalex.org/C44572571","wikidata":"https://www.wikidata.org/wiki/Q7448970","display_name":"SemEval","level":3,"score":0.43127843737602234},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.428725928068161},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.20608681440353394},{"id":"https://openalex.org/C46312422","wikidata":"https://www.wikidata.org/wiki/Q11024","display_name":"Communication","level":1,"score":0.10961788892745972},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/acii.2009.5349598","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acii.2009.5349598","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.47999998927116394}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W38739846","https://openalex.org/W1969769481","https://openalex.org/W2003458432","https://openalex.org/W2014902591","https://openalex.org/W2033702744","https://openalex.org/W2039157612","https://openalex.org/W2075718943","https://openalex.org/W2105468141","https://openalex.org/W2110278938","https://openalex.org/W2118020653","https://openalex.org/W2131510690","https://openalex.org/W2147880316","https://openalex.org/W2166706824","https://openalex.org/W2168493061","https://openalex.org/W2268421884","https://openalex.org/W2395980234","https://openalex.org/W2398854657","https://openalex.org/W2404480901","https://openalex.org/W2949998441","https://openalex.org/W2951278869","https://openalex.org/W3146306708","https://openalex.org/W6601528862","https://openalex.org/W6712710312","https://openalex.org/W6713894373","https://openalex.org/W6763745640","https://openalex.org/W6764146914"],"related_works":["https://openalex.org/W2955987787","https://openalex.org/W1988325893","https://openalex.org/W2252023808","https://openalex.org/W3114765853","https://openalex.org/W2468744590","https://openalex.org/W4385570727","https://openalex.org/W2622126923","https://openalex.org/W2945121592","https://openalex.org/W4308769266","https://openalex.org/W3199829813"],"abstract_inverted_index":{"This":[0],"paper":[1],"reports":[2],"the":[3,24,66,112,126,152,180,185],"mechanism":[4,99],"of":[5,32,87,93,106,111,166,184],"sentence":[6,108,117,142,172],"level":[7,15,52,69,80,118,143,173,187],"emotion":[8,12,34,70,81,114,119,144,149,188],"identification":[9,202],"based":[10,78,97,124,178],"on":[11,23,89,125,179,203],"tagged":[13],"word":[14,51,68,79,186],"constituents":[16],"acquired":[17],"by":[18],"an":[19,85,164],"automatic":[20],"classifier":[21],"applied":[22,102],"SemEval":[25],"2007":[26],"Affect":[27,55],"Sensing":[28],"corpus.":[29],"Basic":[30],"set":[31,92],"six":[33,113],"types,":[35],"namely,":[36],"happy,":[37],"sad,":[38],"anger,":[39],"disgust,":[40],"fear":[41],"and":[42,49,163,192,197],"surprise":[43],"have":[44,57,121,134,156],"been":[45,58,101,122,135,157,169,176],"selected":[46],"for":[47,63,103,109,137,200],"reliable":[48],"semi-automatic":[50,67],"annotation.":[53],"WordNet":[54],"lists":[56],"preprocessed":[59],"using":[60],"SentiWordNet":[61],"information":[62],"use":[64],"in":[65,141],"annotation":[71],"process.":[72],"The":[73,146,171],"Conditional":[74],"Random":[75],"Field":[76],"(CRF)":[77],"classification":[82],"has":[83,100,168,175],"yielded":[84],"accuracy":[86,165],"87.65%":[88],"a":[90,107],"test":[91,161,205],"250":[94,160,204],"sentences.":[95,206],"Sense":[96],"scoring":[98],"calculating":[104],"scores":[105],"each":[110],"types.":[115],"Probable":[116],"tags":[120],"assigned":[123,158],"system":[127],"produced":[128],"ordered":[129],"sense":[130,154,182],"scores.":[131],"Post-processing":[132],"strategies":[133],"adopted":[136],"handling":[138],"negative":[139],"words":[140],"tagging.":[145],"best":[147],"two":[148],"tags,":[150],"with":[151],"maximum":[153],"scores,":[155],"to":[159],"sentences":[162],"67.2%":[167],"achieved.":[170],"valence":[174,201],"calculated":[177],"total":[181],"score":[183],"tags.":[189],"Accuracy,":[190],"precision":[191],"recall":[193],"are":[194],"60.47%,":[195],"67.95":[196],"65.11":[198],"respectively":[199]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
