{"id":"https://openalex.org/W2767770737","doi":"https://doi.org/10.1145/3132847.3133063","title":"Cluster-level Emotion Pattern Matching for Cross-Domain Social Emotion Classification","display_name":"Cluster-level Emotion Pattern Matching for Cross-Domain Social Emotion Classification","publication_year":2017,"publication_date":"2017-11-06","ids":{"openalex":"https://openalex.org/W2767770737","doi":"https://doi.org/10.1145/3132847.3133063","mag":"2767770737"},"language":"en","primary_location":{"id":"doi:10.1145/3132847.3133063","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3132847.3133063","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2017 ACM on Conference on Information and Knowledge Management","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/A5000403642","display_name":"Endong Zhu","orcid":null},"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":"Endong Zhu","raw_affiliation_strings":["Sun Yat-sen University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University, 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":["Sun Yat-sen University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University, 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":["Education University of Hong Kong, Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Education University of Hong Kong, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I4210086892"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100416126","display_name":"Yuwei Liu","orcid":"https://orcid.org/0009-0008-8892-7738"},"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":"Yuwei Liu","raw_affiliation_strings":["Sun Yat-sen University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"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":["Sun Yat-sen University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University, 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, Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Caritas Institute of Higher Education, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I1877545"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5000403642"],"corresponding_institution_ids":["https://openalex.org/I157773358"],"apc_list":null,"apc_paid":null,"fwci":0.195,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.6337366,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"2435","last_page":"2438"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9944000244140625,"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":0.9742000102996826,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.7634115815162659},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7580268979072571},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.652198314666748},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6369478702545166},{"id":"https://openalex.org/keywords/emotion-classification","display_name":"Emotion classification","score":0.5542096495628357},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.551682710647583},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5428221225738525},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4302099943161011},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4280204474925995},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3638947606086731},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35518670082092285},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09008672833442688}],"concepts":[{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.7634115815162659},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7580268979072571},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.652198314666748},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6369478702545166},{"id":"https://openalex.org/C206310091","wikidata":"https://www.wikidata.org/wiki/Q750859","display_name":"Emotion classification","level":2,"score":0.5542096495628357},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.551682710647583},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5428221225738525},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4302099943161011},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4280204474925995},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3638947606086731},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35518670082092285},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09008672833442688},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3132847.3133063","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3132847.3133063","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2017 ACM on Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1977309386","https://openalex.org/W2045631398","https://openalex.org/W2069445814","https://openalex.org/W2105468141","https://openalex.org/W2158108973","https://openalex.org/W2285696530","https://openalex.org/W2523829596","https://openalex.org/W2573073746","https://openalex.org/W4205184193"],"related_works":["https://openalex.org/W1972035260","https://openalex.org/W2794488505","https://openalex.org/W3147584709","https://openalex.org/W4301594054","https://openalex.org/W3125889879","https://openalex.org/W2977677679","https://openalex.org/W3124422538","https://openalex.org/W2295467472","https://openalex.org/W3046451053","https://openalex.org/W1992327129"],"abstract_inverted_index":{"This":[0,78],"paper":[1,79],"addresses":[2],"the":[3,40,46,86,93,98,107],"task":[4,15],"of":[5,10,31,42,63,89,109],"cross-domain":[6,14,51,114],"social":[7,115],"emotion":[8,41,52,87,116],"classification":[9,53],"online":[11],"documents.":[12],"The":[13],"is":[16,71],"formulated":[17],"as":[18],"using":[19],"abundant":[20],"labeled":[21,32],"documents":[22,33,44,91],"from":[23,34],"a":[24,28,35,67,81],"source":[25],"domain":[26],"and":[27],"small":[29],"amount":[30],"target":[36,47],"domain,":[37],"to":[38,73,96],"predict":[39],"unlabeled":[43],"in":[45,75],"domain.":[48],"Although":[49],"several":[50],"algorithms":[54],"have":[55],"been":[56],"proposed,":[57],"they":[58],"require":[59],"that":[60],"feature":[61],"distributions":[62],"different":[64],"domains":[65],"share":[66],"sufficient":[68],"overlapping,":[69],"which":[70,84],"hard":[72],"meet":[74],"practical":[76],"applications.":[77],"proposes":[80],"novel":[82],"framework,":[83],"uses":[85],"distribution":[88],"training":[90],"at":[92],"cluster":[94],"level,":[95],"alleviate":[97],"aforementioned":[99],"issue.":[100],"Experimental":[101],"results":[102],"on":[103,113],"two":[104],"datasets":[105],"show":[106],"effectiveness":[108],"our":[110],"proposed":[111],"model":[112],"classification.":[117]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
