{"id":"https://openalex.org/W3010625209","doi":"https://doi.org/10.1177/0165551520910032","title":"Semisupervised sentiment analysis method for online text reviews","display_name":"Semisupervised sentiment analysis method for online text reviews","publication_year":2020,"publication_date":"2020-03-01","ids":{"openalex":"https://openalex.org/W3010625209","doi":"https://doi.org/10.1177/0165551520910032","mag":"3010625209"},"language":"en","primary_location":{"id":"doi:10.1177/0165551520910032","is_oa":false,"landing_page_url":"https://doi.org/10.1177/0165551520910032","pdf_url":null,"source":{"id":"https://openalex.org/S68913162","display_name":"Journal of Information Science","issn_l":"0165-5515","issn":["0165-5515","1741-6485"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320017","host_organization_name":"SAGE Publishing","host_organization_lineage":["https://openalex.org/P4310320017"],"host_organization_lineage_names":["SAGE Publishing"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Information Science","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/A5045956362","display_name":"Gyeong Taek Lee","orcid":"https://orcid.org/0000-0003-4316-3072"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Gyeong Taek Lee","raw_affiliation_strings":["Yonsei University, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yonsei University, Republic of Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001540138","display_name":"Chang Ouk Kim","orcid":"https://orcid.org/0000-0002-6936-5409"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Chang Ouk Kim","raw_affiliation_strings":["Yonsei University, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0002-6936-5409","affiliations":[{"raw_affiliation_string":"Yonsei University, Republic of Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045749444","display_name":"Min Song","orcid":"https://orcid.org/0000-0003-3255-1600"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Min Song","raw_affiliation_strings":["Yonsei University, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0003-3255-1600","affiliations":[{"raw_affiliation_string":"Yonsei University, Republic of Korea","institution_ids":["https://openalex.org/I193775966"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5001540138"],"corresponding_institution_ids":["https://openalex.org/I193775966"],"apc_list":null,"apc_paid":null,"fwci":1.9025,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.88670715,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"47","issue":"3","first_page":"387","last_page":"403"},"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/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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9973000288009644,"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":0.8164202570915222},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.8112279176712036},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7444033026695251},{"id":"https://openalex.org/keywords/word2vec","display_name":"Word2vec","score":0.6762881875038147},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5954105257987976},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5936039686203003},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.5361466407775879},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.48619788885116577},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.4836767613887787},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.44732049107551575},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.4469022750854492},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.4324575364589691},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.42878738045692444},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.26950111985206604}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8164202570915222},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.8112279176712036},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7444033026695251},{"id":"https://openalex.org/C2776461190","wikidata":"https://www.wikidata.org/wiki/Q22673982","display_name":"Word2vec","level":3,"score":0.6762881875038147},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5954105257987976},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5936039686203003},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.5361466407775879},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.48619788885116577},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.4836767613887787},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.44732049107551575},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.4469022750854492},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.4324575364589691},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.42878738045692444},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.26950111985206604},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1177/0165551520910032","is_oa":false,"landing_page_url":"https://doi.org/10.1177/0165551520910032","pdf_url":null,"source":{"id":"https://openalex.org/S68913162","display_name":"Journal of Information Science","issn_l":"0165-5515","issn":["0165-5515","1741-6485"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320017","host_organization_name":"SAGE Publishing","host_organization_lineage":["https://openalex.org/P4310320017"],"host_organization_lineage_names":["SAGE Publishing"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Information Science","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.5099999904632568}],"awards":[{"id":"https://openalex.org/G3341549647","display_name":null,"funder_award_id":"NRF-2018S1A3A2075114","funder_id":"https://openalex.org/F4320321408","funder_display_name":"Ministry of Education"}],"funders":[{"id":"https://openalex.org/F4320321408","display_name":"Ministry of Education","ror":"https://ror.org/01p262204"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1832693441","https://openalex.org/W1975428268","https://openalex.org/W1979432867","https://openalex.org/W2005624335","https://openalex.org/W2046858834","https://openalex.org/W2063596712","https://openalex.org/W2068451972","https://openalex.org/W2084046180","https://openalex.org/W2095579012","https://openalex.org/W2095655043","https://openalex.org/W2143455647","https://openalex.org/W2144874182","https://openalex.org/W2171033594","https://openalex.org/W2187089797","https://openalex.org/W2278629362","https://openalex.org/W2335703454","https://openalex.org/W2346554894","https://openalex.org/W2531190898","https://openalex.org/W2546935677","https://openalex.org/W2560674852","https://openalex.org/W2614322402","https://openalex.org/W2615497679","https://openalex.org/W2791275011","https://openalex.org/W2883123498","https://openalex.org/W2912172494","https://openalex.org/W2930957955","https://openalex.org/W4246154067","https://openalex.org/W6674489603"],"related_works":["https://openalex.org/W4312414840","https://openalex.org/W2794908468","https://openalex.org/W4206276646","https://openalex.org/W2943467239","https://openalex.org/W1571801203","https://openalex.org/W101422005","https://openalex.org/W192740413","https://openalex.org/W3004135598","https://openalex.org/W2952937263","https://openalex.org/W2131153761"],"abstract_inverted_index":{"Sentiment":[0],"analysis":[1,26],"plays":[2],"an":[3,156],"important":[4],"role":[5],"in":[6,11,149,173,185],"understanding":[7],"individual":[8],"opinions":[9,35],"expressed":[10],"websites":[12],"such":[13],"as":[14],"social":[15],"media":[16],"and":[17,36,60],"product":[18],"review":[19],"sites.":[20],"The":[21,46,68,122,144],"common":[22],"approaches":[23],"to":[24,63,76,95,178,203],"sentiment":[25,79,128,168],"use":[27],"the":[28,78,150,167,171,174,179,186,195,198],"sentiments":[29],"carried":[30],"by":[31],"words":[32,147,172,180],"that":[33,108,181,194,204],"express":[34],"are":[37,153,176],"based":[38],"on":[39,210],"either":[40],"supervised":[41,69,206],"or":[42],"unsupervised":[43,47],"learning":[44,48,70,74,159,207],"techniques.":[45],"approach":[49,71,107],"builds":[50,125],"a":[51,65,85,97,105,126,131,136,162],"word-sentiment":[52],"dictionary,":[53],"but":[54],"it":[55],"requires":[56,88],"lengthy":[57],"time":[58],"periods":[59],"high":[61],"costs":[62],"build":[64],"reliable":[66],"dictionary.":[67],"uses":[72],"machine":[73],"models":[75,208],"learn":[77],"scores":[80,145],"of":[81,91,116,146,170,197,205],"words;":[82],"however,":[83],"training":[84,133,151,187],"classifier":[86],"model":[87,139,165],"large":[89,211],"amounts":[90,115],"labelled":[92,117],"text":[93],"data":[94,118],"achieve":[96],"good":[98],"performance.":[99],"In":[100,161],"this":[101],"article,":[102],"we":[103,192],"propose":[104],"semisupervised":[106],"performs":[109],"well":[110],"despite":[111],"having":[112],"only":[113],"small":[114,132],"available":[119],"for":[120],"training.":[121],"proposed":[123,199],"method":[124,200],"base":[127],"dictionary":[129,175],"from":[130],"dataset":[134,152],"using":[135,155],"lasso-based":[137],"ensemble":[138],"with":[140],"minimal":[141],"human":[142],"effort.":[143],"not":[148,183],"estimated":[154],"adaptive":[157],"instance-based":[158],"model.":[160],"pretrained":[163],"word2vec":[164],"space,":[166],"values":[169],"propagated":[177],"did":[182],"exist":[184],"dataset.":[188],"Through":[189],"two":[190],"experiments,":[191],"demonstrate":[193],"performance":[196],"is":[201],"comparable":[202],"trained":[209],"datasets.":[212]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
