{"id":"https://openalex.org/W2964225211","doi":"https://doi.org/10.18653/v1/s18-1019","title":"AttnConvnet at SemEval-2018 Task 1: Attention-based Convolutional Neural Networks for Multi-label Emotion Classification","display_name":"AttnConvnet at SemEval-2018 Task 1: Attention-based Convolutional Neural Networks for Multi-label Emotion Classification","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2964225211","doi":"https://doi.org/10.18653/v1/s18-1019","mag":"2964225211"},"language":"en","primary_location":{"id":"doi:10.18653/v1/s18-1019","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s18-1019","pdf_url":"https://www.aclweb.org/anthology/S18-1019.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 12th 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/S18-1019.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037342367","display_name":"Yanghoon Kim","orcid":"https://orcid.org/0000-0002-6939-9537"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yanghoon Kim","raw_affiliation_strings":["Automation and Systems Research Institute, Seoul National University, Seoul, Korea","Seoul National University, Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"Automation and Systems Research Institute, Seoul National University, Seoul, Korea","institution_ids":["https://openalex.org/I139264467"]},{"raw_affiliation_string":"Seoul National University, Seoul, Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063029769","display_name":"Hwanhee Lee","orcid":"https://orcid.org/0000-0002-9367-9811"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hwanhee Lee","raw_affiliation_strings":["Seoul National University, Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"Seoul National University, Seoul, Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077832834","display_name":"Kyomin Jung","orcid":"https://orcid.org/0000-0003-2547-7051"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Kyomin Jung","raw_affiliation_strings":["Automation and Systems Research Institute, Seoul National University, Seoul, Korea","Seoul National University, Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"Automation and Systems Research Institute, Seoul National University, Seoul, Korea","institution_ids":["https://openalex.org/I139264467"]},{"raw_affiliation_string":"Seoul National University, Seoul, Korea","institution_ids":["https://openalex.org/I139264467"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5077832834"],"corresponding_institution_ids":["https://openalex.org/I139264467"],"apc_list":null,"apc_paid":null,"fwci":4.9074,"has_fulltext":true,"cited_by_count":47,"citation_normalized_percentile":{"value":0.9612537,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"141","last_page":"145"},"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/T10028","display_name":"Topic Modeling","score":0.9987000226974487,"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":0.9952999949455261,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/semeval","display_name":"SemEval","score":0.8797388076782227},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8525760173797607},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.7286668419837952},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6800194978713989},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5951653718948364},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5945018529891968},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5853261947631836},{"id":"https://openalex.org/keywords/emoji","display_name":"Emoji","score":0.5788009166717529},{"id":"https://openalex.org/keywords/lexicon","display_name":"Lexicon","score":0.5648431181907654},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5338517427444458},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4963987469673157},{"id":"https://openalex.org/keywords/wordnet","display_name":"WordNet","score":0.4302200675010681},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.06833386421203613}],"concepts":[{"id":"https://openalex.org/C44572571","wikidata":"https://www.wikidata.org/wiki/Q7448970","display_name":"SemEval","level":3,"score":0.8797388076782227},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8525760173797607},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.7286668419837952},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6800194978713989},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5951653718948364},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5945018529891968},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5853261947631836},{"id":"https://openalex.org/C2779247141","wikidata":"https://www.wikidata.org/wiki/Q1049294","display_name":"Emoji","level":3,"score":0.5788009166717529},{"id":"https://openalex.org/C2778121359","wikidata":"https://www.wikidata.org/wiki/Q8096","display_name":"Lexicon","level":2,"score":0.5648431181907654},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5338517427444458},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4963987469673157},{"id":"https://openalex.org/C157659113","wikidata":"https://www.wikidata.org/wiki/Q533822","display_name":"WordNet","level":2,"score":0.4302200675010681},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.06833386421203613},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","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},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/s18-1019","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s18-1019","pdf_url":"https://www.aclweb.org/anthology/S18-1019.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 12th International Workshop on Semantic Evaluation","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/s18-1019","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s18-1019","pdf_url":"https://www.aclweb.org/anthology/S18-1019.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 12th International Workshop on Semantic Evaluation","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.6000000238418579,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G1103364132","display_name":null,"funder_award_id":"10073144","funder_id":"https://openalex.org/F4320321681","funder_display_name":"Ministry of Trade, Industry and Energy"},{"id":"https://openalex.org/G626505518","display_name":null,"funder_award_id":"No. 201","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G8265331568","display_name":null,"funder_award_id":"2016M3C4A7952632","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G8582691448","display_name":null,"funder_award_id":"MOTIE, Korea","funder_id":"https://openalex.org/F4320321681","funder_display_name":"Ministry of Trade, Industry and Energy"}],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320321681","display_name":"Ministry of Trade, Industry and Energy","ror":"https://ror.org/008nkqk13"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"},{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2964225211.pdf","grobid_xml":"https://content.openalex.org/works/W2964225211.grobid-xml"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W1832693441","https://openalex.org/W2040467972","https://openalex.org/W2064675550","https://openalex.org/W2133564696","https://openalex.org/W2143017621","https://openalex.org/W2153579005","https://openalex.org/W2154071538","https://openalex.org/W2250539671","https://openalex.org/W2402268235","https://openalex.org/W2493916176","https://openalex.org/W2805744755","https://openalex.org/W2953320089","https://openalex.org/W2963216553","https://openalex.org/W2963403868","https://openalex.org/W2964308564","https://openalex.org/W4290662212","https://openalex.org/W4294170691","https://openalex.org/W4385245566"],"related_works":["https://openalex.org/W1988325893","https://openalex.org/W2770617756","https://openalex.org/W2252023808","https://openalex.org/W3114765853","https://openalex.org/W2807533849","https://openalex.org/W2805057102","https://openalex.org/W4385570727","https://openalex.org/W2805627106","https://openalex.org/W2468744590","https://openalex.org/W2622126923"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,40],"propose":[4],"an":[5],"attention-based":[6],"classifier":[7],"that":[8],"predicts":[9],"multiple":[10],"emotions":[11],"of":[12,22,61],"a":[13],"given":[14,68],"sentence.":[15],"Our":[16,70],"model":[17,44,51,71],"imitates":[18],"human's":[19],"two-step":[20],"procedure":[21],"sentence":[23,60],"understanding":[24],"and":[25,30,36,48],"it":[26],"can":[27],"effectively":[28],"represent":[29],"classify":[31],"sentences.":[32],"With":[33],"emoji-to-meaning":[34],"preprocessing":[35],"extra":[37],"lexicon":[38],"utilization,":[39],"further":[41],"improve":[42],"the":[43],"performance.":[45],"We":[46],"train":[47],"evaluate":[49],"our":[50],"with":[52],"data":[53],"provided":[54],"by":[55],"SemEval-2018":[56],"task":[57],"1-5,":[58],"each":[59],"which":[62],"has":[63],"several":[64],"labels":[65],"among":[66],"11":[67],"emotions.":[69],"achieves":[72],"5th/1st":[73],"rank":[74],"in":[75],"English/Spanish":[76],"respectively.":[77]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":5}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}
