{"id":"https://openalex.org/W2708418680","doi":"https://doi.org/10.1109/taffc.2017.2716930","title":"Bootstrapping Social Emotion Classification with Semantically Rich Hybrid Neural Networks","display_name":"Bootstrapping Social Emotion Classification with Semantically Rich Hybrid Neural Networks","publication_year":2017,"publication_date":"2017-06-19","ids":{"openalex":"https://openalex.org/W2708418680","doi":"https://doi.org/10.1109/taffc.2017.2716930","mag":"2708418680"},"language":"en","primary_location":{"id":"doi:10.1109/taffc.2017.2716930","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taffc.2017.2716930","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/A5101511516","display_name":"Xiangsheng Li","orcid":"https://orcid.org/0009-0001-1683-7054"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiangsheng Li","raw_affiliation_strings":["School of Data and Computer Science, Sun Yat-sen University, No. 132 Waihuan East Rd., Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Data and Computer Science, Sun Yat-sen University, No. 132 Waihuan East Rd., Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058291454","display_name":"Yanghui Rao","orcid":"https://orcid.org/0000-0003-1610-9599"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanghui Rao","raw_affiliation_strings":["School of Data and Computer Science, Sun Yat-sen University, No. 132 Waihuan East Rd., Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Data and Computer Science, Sun Yat-sen University, No. 132 Waihuan East Rd., Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013151488","display_name":"Haoran Xie","orcid":"https://orcid.org/0000-0003-0965-3617"},"institutions":[{"id":"https://openalex.org/I4210086892","display_name":"Education University of Hong Kong","ror":"https://ror.org/000t0f062","country_code":"HK","type":"education","lineage":["https://openalex.org/I4210086892"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Haoran Xie","raw_affiliation_strings":["Department of Mathematics and Information Technology, The Education University of Hong Kong, Tai Po, Hong Kong SAR"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Information Technology, The Education University of Hong Kong, Tai Po, Hong Kong SAR","institution_ids":["https://openalex.org/I4210086892"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084348345","display_name":"Raymond Y.K. Lau","orcid":"https://orcid.org/0000-0002-5751-4550"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Raymond Yiu Keung Lau","raw_affiliation_strings":["Department of Information Systems, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong SAR"],"affiliations":[{"raw_affiliation_string":"Department of Information Systems, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong SAR","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017205177","display_name":"Jian Yin","orcid":"https://orcid.org/0000-0002-1214-5384"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Yin","raw_affiliation_strings":["School of Data and Computer Science, Sun Yat-sen University, No. 132 Waihuan East Rd., Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Data and Computer Science, Sun Yat-sen University, No. 132 Waihuan East Rd., Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072482402","display_name":"Fu Lee Wang","orcid":"https://orcid.org/0000-0002-3976-0053"},"institutions":[{"id":"https://openalex.org/I1877545","display_name":"Saint Francis University","ror":"https://ror.org/01wcz2f33","country_code":"HK","type":"education","lineage":["https://openalex.org/I1877545"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Fu Lee Wang","raw_affiliation_strings":["Caritas Institute of Higher Education, Tseung Kwan O, Hong Kong SAR"],"affiliations":[{"raw_affiliation_string":"Caritas Institute of Higher Education, Tseung Kwan O, Hong Kong SAR","institution_ids":["https://openalex.org/I1877545"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5101511516"],"corresponding_institution_ids":["https://openalex.org/I157773358"],"apc_list":null,"apc_paid":null,"fwci":6.6048,"has_fulltext":false,"cited_by_count":53,"citation_normalized_percentile":{"value":0.97219838,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"8","issue":"4","first_page":"428","last_page":"442"},"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":0.9976999759674072,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9973999857902527,"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/interpretability","display_name":"Interpretability","score":0.9169156551361084},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7555959224700928},{"id":"https://openalex.org/keywords/bootstrapping","display_name":"Bootstrapping (finance)","score":0.7067463397979736},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6741317510604858},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.6573551893234253},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6206240653991699},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5801539421081543},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5325739979743958},{"id":"https://openalex.org/keywords/emotion-classification","display_name":"Emotion classification","score":0.47195568680763245},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.450194388628006},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.444385826587677},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4440712630748749},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.44319653511047363},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.32226598262786865}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.9169156551361084},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7555959224700928},{"id":"https://openalex.org/C207609745","wikidata":"https://www.wikidata.org/wiki/Q4944086","display_name":"Bootstrapping (finance)","level":2,"score":0.7067463397979736},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6741317510604858},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.6573551893234253},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6206240653991699},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5801539421081543},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5325739979743958},{"id":"https://openalex.org/C206310091","wikidata":"https://www.wikidata.org/wiki/Q750859","display_name":"Emotion classification","level":2,"score":0.47195568680763245},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.450194388628006},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.444385826587677},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4440712630748749},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.44319653511047363},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.32226598262786865},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C106159729","wikidata":"https://www.wikidata.org/wiki/Q2294553","display_name":"Financial economics","level":1,"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/taffc.2017.2716930","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taffc.2017.2716930","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":[{"display_name":"Quality Education","score":0.6000000238418579,"id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G1941139581","display_name":null,"funder_award_id":"U1611264","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4044104431","display_name":null,"funder_award_id":"U1401256","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5229126207","display_name":null,"funder_award_id":"61472453","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7888934241","display_name":null,"funder_award_id":"61502545","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8698608195","display_name":null,"funder_award_id":"U1501252","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320309893","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321160","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71"},{"id":"https://openalex.org/F4320321592","display_name":"Research Grants Council, University Grants Committee","ror":"https://ror.org/00djwmt25"},{"id":"https://openalex.org/F4320322170","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86"},{"id":"https://openalex.org/F4320326972","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":99,"referenced_works":["https://openalex.org/W304145884","https://openalex.org/W1502922572","https://openalex.org/W1532325895","https://openalex.org/W1554348720","https://openalex.org/W1659986917","https://openalex.org/W1746819321","https://openalex.org/W1821462560","https://openalex.org/W1880262756","https://openalex.org/W1970381522","https://openalex.org/W1972095489","https://openalex.org/W1999320905","https://openalex.org/W2001082470","https://openalex.org/W2001614588","https://openalex.org/W2028140375","https://openalex.org/W2039797899","https://openalex.org/W2045599215","https://openalex.org/W2045631398","https://openalex.org/W2048195127","https://openalex.org/W2050752817","https://openalex.org/W2062522089","https://openalex.org/W2072007696","https://openalex.org/W2075187489","https://openalex.org/W2084374738","https://openalex.org/W2087122779","https://openalex.org/W2100002341","https://openalex.org/W2100495367","https://openalex.org/W2102471052","https://openalex.org/W2103626435","https://openalex.org/W2104090402","https://openalex.org/W2105468141","https://openalex.org/W2108665656","https://openalex.org/W2110798204","https://openalex.org/W2112812053","https://openalex.org/W2113533029","https://openalex.org/W2113606819","https://openalex.org/W2116064496","https://openalex.org/W2120354757","https://openalex.org/W2122922389","https://openalex.org/W2133257461","https://openalex.org/W2138857742","https://openalex.org/W2141599568","https://openalex.org/W2147152072","https://openalex.org/W2147768505","https://openalex.org/W2153579005","https://openalex.org/W2165644552","https://openalex.org/W2165698076","https://openalex.org/W2166096645","https://openalex.org/W2172174689","https://openalex.org/W2250539671","https://openalex.org/W2251028926","https://openalex.org/W2285696530","https://openalex.org/W2288325796","https://openalex.org/W2295582178","https://openalex.org/W2296229202","https://openalex.org/W2306941105","https://openalex.org/W2339611261","https://openalex.org/W2342045095","https://openalex.org/W2546191734","https://openalex.org/W2552446604","https://openalex.org/W2573073746","https://openalex.org/W2604268533","https://openalex.org/W2605998369","https://openalex.org/W2606321545","https://openalex.org/W2613634265","https://openalex.org/W2616180702","https://openalex.org/W2962842434","https://openalex.org/W2962994101","https://openalex.org/W2963043971","https://openalex.org/W2963632944","https://openalex.org/W3037515705","https://openalex.org/W3146885639","https://openalex.org/W4211049957","https://openalex.org/W4213009331","https://openalex.org/W4229739354","https://openalex.org/W4294170691","https://openalex.org/W4296976275","https://openalex.org/W6637057313","https://openalex.org/W6638523607","https://openalex.org/W6639619044","https://openalex.org/W6674813771","https://openalex.org/W6676231525","https://openalex.org/W6676481782","https://openalex.org/W6676903177","https://openalex.org/W6676943302","https://openalex.org/W6677055134","https://openalex.org/W6679718588","https://openalex.org/W6680300913","https://openalex.org/W6680890276","https://openalex.org/W6682691769","https://openalex.org/W6684671274","https://openalex.org/W6684753728","https://openalex.org/W6696727771","https://openalex.org/W6697261957","https://openalex.org/W6697274609","https://openalex.org/W6731568869","https://openalex.org/W6736176650","https://openalex.org/W6736430770","https://openalex.org/W6779800811","https://openalex.org/W6837117956"],"related_works":["https://openalex.org/W2905433371","https://openalex.org/W2888392564","https://openalex.org/W4310278675","https://openalex.org/W4388422664","https://openalex.org/W4390569940","https://openalex.org/W4361193272","https://openalex.org/W2963326959","https://openalex.org/W4388685194","https://openalex.org/W4312407344","https://openalex.org/W2025635341"],"abstract_inverted_index":{"Social":[0],"emotion":[1,52,94,163,191],"classification":[2,53,95,164,192],"aims":[3],"to":[4,68,87,128,137,160],"predict":[5],"the":[6,50,58,110,134,150,183],"aggregation":[7],"of":[8,79,82,102,112,116,154],"emotional":[9],"responses":[10],"embedded":[11],"in":[12,106],"online":[13,38],"comments":[14,39],"contributed":[15],"by":[16,43],"various":[17],"users.":[18],"Such":[19],"a":[20,33,44,113],"task":[21,54],"is":[22,32,109,149],"inherently":[23],"challenging":[24],"because":[25,78],"extracting":[26],"relevant":[27],"semantics":[28,156],"from":[29],"free":[30],"texts":[31],"classical":[34],"research":[35],"problem.":[36],"Moreover,":[37],"are":[40],"typically":[41],"characterized":[42],"sparse":[45,84],"feature":[46],"space,":[47],"which":[48,123],"makes":[49],"corresponding":[51],"very":[55],"difficult.":[56],"On":[57],"other":[59,189],"hand,":[60],"though":[61],"deep":[62],"neural":[63,120,135,158,186],"networks":[64,159,187],"have":[65],"been":[66],"shown":[67],"be":[69],"effective":[70],"for":[71],"speech":[72],"recognition":[73],"and":[74,142,165],"image":[75],"analysis":[76],"tasks":[77],"their":[80,91],"capabilities":[81],"transforming":[83],"low-level":[85],"features":[86],"dense":[88],"high-level":[89],"features,":[90],"effectiveness":[92],"on":[93,172],"requires":[96],"further":[97],"investigation.":[98],"The":[99],"main":[100],"contribution":[101],"our":[103,145,178],"work":[104,153],"reported":[105],"this":[107,148],"paper":[108],"development":[111],"novel":[114],"model":[115],"semantically":[117],"rich":[118],"hybrid":[119,185],"network":[121,136,166],"(HNN)":[122],"leverages":[124],"unsupervised":[125],"teaching":[126],"models":[127],"incorporate":[129],"semantic":[130],"domain":[131],"knowledge":[132],"into":[133,157],"bootstrap":[138],"its":[139],"inference":[140],"power":[141],"interpretability.":[143,167],"To":[144],"best":[146],"knowledge,":[147],"first":[151],"successful":[152],"incorporating":[155],"enhance":[161],"social":[162,175],"Through":[168],"empirical":[169],"studies":[170],"based":[171],"three":[173],"real-world":[174],"media":[176],"datasets,":[177],"experimental":[179],"results":[180],"confirm":[181],"that":[182],"proposed":[184],"outperform":[188],"state-of-the-art":[190],"methods.":[193]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":15},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":8}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
