{"id":"https://openalex.org/W2976790809","doi":"https://doi.org/10.1109/bigdataservice.2019.00030","title":"Sentiment Analysis of Chinese Product Reviews using Gated Recurrent Unit","display_name":"Sentiment Analysis of Chinese Product Reviews using Gated Recurrent Unit","publication_year":2019,"publication_date":"2019-04-01","ids":{"openalex":"https://openalex.org/W2976790809","doi":"https://doi.org/10.1109/bigdataservice.2019.00030","mag":"2976790809"},"language":"en","primary_location":{"id":"doi:10.1109/bigdataservice.2019.00030","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdataservice.2019.00030","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Fifth International Conference on Big Data Computing Service and Applications (BigDataService)","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/A5077344237","display_name":"Jun Sheng Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Jun Sheng Lee","raw_affiliation_strings":["Business Analytics Centre, National University of Singapore, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"Business Analytics Centre, National University of Singapore, Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067426042","display_name":"Denis Zuba","orcid":null},"institutions":[{"id":"https://openalex.org/I4210148785","display_name":"Logitech (Switzerland)","ror":"https://ror.org/05pkpss54","country_code":"CH","type":"company","lineage":["https://openalex.org/I4210148785"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Denis Zuba","raw_affiliation_strings":["Data Science & Advanced Analytics, Logitech Europe S.A., Lausanne, Switzerland"],"affiliations":[{"raw_affiliation_string":"Data Science & Advanced Analytics, Logitech Europe S.A., Lausanne, Switzerland","institution_ids":["https://openalex.org/I4210148785"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081395110","display_name":"Yan Pang","orcid":"https://orcid.org/0000-0002-7315-1358"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Yan Pang","raw_affiliation_strings":["Department of Analytics and Operations, National University of Singapore, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"Department of Analytics and Operations, National University of Singapore, Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5077344237"],"corresponding_institution_ids":["https://openalex.org/I165932596"],"apc_list":null,"apc_paid":null,"fwci":1.6802,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.88480008,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"28","issue":null,"first_page":"173","last_page":"181"},"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.995199978351593,"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":0.9925000071525574,"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/sentiment-analysis","display_name":"Sentiment analysis","score":0.8574256896972656},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7792383432388306},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6840449571609497},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.6758702993392944},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6503217220306396},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.6310679912567139},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.627065122127533},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.4424108862876892},{"id":"https://openalex.org/keywords/empirical-research","display_name":"Empirical research","score":0.4176924228668213},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10026299953460693},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07919085025787354}],"concepts":[{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.8574256896972656},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7792383432388306},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6840449571609497},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.6758702993392944},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6503217220306396},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.6310679912567139},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.627065122127533},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.4424108862876892},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.4176924228668213},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10026299953460693},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07919085025787354},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdataservice.2019.00030","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdataservice.2019.00030","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Fifth International Conference on Big Data Computing Service and Applications (BigDataService)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.699999988079071,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W13254153","https://openalex.org/W122553268","https://openalex.org/W1565863475","https://openalex.org/W1577366066","https://openalex.org/W1614298861","https://openalex.org/W1924770834","https://openalex.org/W2012070465","https://openalex.org/W2064675550","https://openalex.org/W2071332064","https://openalex.org/W2077563243","https://openalex.org/W2096707493","https://openalex.org/W2096790918","https://openalex.org/W2097726431","https://openalex.org/W2107878631","https://openalex.org/W2130325614","https://openalex.org/W2133564696","https://openalex.org/W2139979941","https://openalex.org/W2157331557","https://openalex.org/W2160660844","https://openalex.org/W2166706824","https://openalex.org/W2186930719","https://openalex.org/W2199803028","https://openalex.org/W2251939518","https://openalex.org/W2252215182","https://openalex.org/W2289405268","https://openalex.org/W2313494261","https://openalex.org/W2415969251","https://openalex.org/W2424238744","https://openalex.org/W2468684362","https://openalex.org/W2611614234","https://openalex.org/W2746802549","https://openalex.org/W2787893582","https://openalex.org/W2949998441","https://openalex.org/W2950577311","https://openalex.org/W2951278869","https://openalex.org/W2964308564","https://openalex.org/W3146306708","https://openalex.org/W4205184193","https://openalex.org/W6600530165","https://openalex.org/W6604970484","https://openalex.org/W6633918527","https://openalex.org/W6636510571","https://openalex.org/W6640212811","https://openalex.org/W6674489603","https://openalex.org/W6679434410","https://openalex.org/W6687724439","https://openalex.org/W6691459498","https://openalex.org/W6720006281","https://openalex.org/W6742674470","https://openalex.org/W6763745640","https://openalex.org/W6764146914"],"related_works":["https://openalex.org/W2931688134","https://openalex.org/W2377919138","https://openalex.org/W2378857091","https://openalex.org/W103652678","https://openalex.org/W4226090359","https://openalex.org/W2059697060","https://openalex.org/W936373746","https://openalex.org/W2975817033","https://openalex.org/W4382701072","https://openalex.org/W4256502920"],"abstract_inverted_index":{"Despite":[0],"the":[1,14,33,42,54,61,116],"explosive":[2],"growth":[3],"of":[4,17,36,45,56,64,87,95,105,112,120],"Chinese":[5,18,46],"e-commerce":[6],"platforms":[7],"in":[8,21,41,60],"recent":[9],"years,":[10],"research":[11],"focusing":[12],"on":[13,77,99],"sentiment":[15,62],"classification":[16,73],"documents":[19],"pales":[20],"comparison":[22],"to":[23,67],"its":[24],"western":[25],"counterparts":[26],"(English":[27],"documents).":[28],"This":[29],"paper":[30],"looks":[31],"into":[32],"nascent":[34],"area":[35],"Natural":[37],"Language":[38],"Processing":[39],"(NLP)":[40],"Sentiment":[43],"Analysis":[44],"Text.":[47],"The":[48],"proposed":[49,122],"Deep":[50],"Learning":[51],"method":[52],"is":[53],"use":[55],"a":[57,78],"sentence-based":[58],"approach":[59],"analysis":[63],"online":[65],"reviews":[66,90,108],"gain":[68],"more":[69],"granularity":[70],"and":[71,118],"increased":[72],"accuracy.":[74],"Experimental":[75],"results":[76,98],"balanced":[79],"(50:50),":[80],"2":[81],"class":[82],"(positive,":[83],"negative)":[84],"test":[85,103],"dataset":[86,104],"1669":[88],"product":[89,107],"show":[91,109],"an":[92,100,110],"empirical":[93],"accuracy":[94,111],"87.66%,":[96],"while":[97],"imbalanced":[101],"(18:82)":[102],"2519":[106],"87.9%,":[113],"thus":[114],"demonstrating":[115],"effectiveness":[117],"robustness":[119],"this":[121],"approach.":[123]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}