{"id":"https://openalex.org/W2485378233","doi":"https://doi.org/10.1109/snpd.2016.7515884","title":"A hybrid method for bilingual text sentiment classification based on deep learning","display_name":"A hybrid method for bilingual text sentiment classification based on deep learning","publication_year":2016,"publication_date":"2016-05-01","ids":{"openalex":"https://openalex.org/W2485378233","doi":"https://doi.org/10.1109/snpd.2016.7515884","mag":"2485378233"},"language":"en","primary_location":{"id":"doi:10.1109/snpd.2016.7515884","is_oa":false,"landing_page_url":"https://doi.org/10.1109/snpd.2016.7515884","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 17th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","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/A5101462397","display_name":"Guolong Liu","orcid":"https://orcid.org/0000-0002-3726-4216"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Guolong Liu","raw_affiliation_strings":["School of Computer and Information Science, Southwest University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Information Science, Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101453596","display_name":"Xiaofei Xu","orcid":"https://orcid.org/0000-0002-9492-0312"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaofei Xu","raw_affiliation_strings":["School of Computer and Information Science, Southwest University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Information Science, Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013896126","display_name":"Bailong Deng","orcid":null},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bailong Deng","raw_affiliation_strings":["School of Computer and Information Science, Southwest University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Information Science, Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001677796","display_name":"Siding Chen","orcid":"https://orcid.org/0009-0005-8669-7842"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Siding Chen","raw_affiliation_strings":["School of Computer and Information Science, Southwest University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Information Science, Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100360960","display_name":"Li Li","orcid":"https://orcid.org/0000-0001-5065-6022"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Li","raw_affiliation_strings":["School of Computer and Information Science, Southwest University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Information Science, Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101462397"],"corresponding_institution_ids":["https://openalex.org/I142108993"],"apc_list":null,"apc_paid":null,"fwci":1.7139,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.88913264,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9995999932289124,"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":0.9995999932289124,"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":0.996399998664856,"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":0.9957000017166138,"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":0.823775053024292},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.7755178213119507},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.765160083770752},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6114868521690369},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.6058065295219421},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5720285773277283},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5198726654052734},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5008044242858887},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.48293229937553406},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4605293869972229}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.823775053024292},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.7755178213119507},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.765160083770752},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6114868521690369},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.6058065295219421},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5720285773277283},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5198726654052734},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5008044242858887},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.48293229937553406},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4605293869972229},{"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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/snpd.2016.7515884","is_oa":false,"landing_page_url":"https://doi.org/10.1109/snpd.2016.7515884","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 17th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4399999976158142,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W179875071","https://openalex.org/W2097726431","https://openalex.org/W2111305191","https://openalex.org/W2117130368","https://openalex.org/W2119188197","https://openalex.org/W2122585011","https://openalex.org/W2132339004","https://openalex.org/W2144499799","https://openalex.org/W2154359981","https://openalex.org/W2166706824","https://openalex.org/W2171928131","https://openalex.org/W2251939518","https://openalex.org/W2950577311","https://openalex.org/W4205184193","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W3107474891","https://openalex.org/W4223943233","https://openalex.org/W2952639376","https://openalex.org/W2953332970","https://openalex.org/W3129712087","https://openalex.org/W2922457425","https://openalex.org/W2886884189","https://openalex.org/W3192794374","https://openalex.org/W3105191672","https://openalex.org/W2741836081"],"abstract_inverted_index":{"Text":[0],"sentiment":[1,9,28,83,89,124],"classification":[2,29,84,90,125],"has":[3],"occupied":[4],"a":[5,58,135,177],"pivotal":[6],"position":[7],"in":[8,55,123],"analysis":[10],"research,":[11],"it":[12],"offers":[13],"important":[14],"opinion":[15],"mining":[16],"functions.":[17],"Nowadays,":[18],"with":[19,100,199],"explosion":[20],"of":[21,34,149,202,205],"information,":[22],"many":[23],"researchers":[24],"are":[25,51,115,120,144],"focusing":[26],"on":[27,31,185],"research":[30,49],"massive":[32],"amounts":[33],"data.":[35],"However,":[36],"the":[37,63,131,139,147,156,162,181,186,191,200,203],"traditional":[38],"machine":[39],"learning":[40,65,69],"methods":[41,133,183],"cannot":[42],"acquire":[43],"text":[44,82,88],"semantic":[45],"information":[46],"and":[47,67,113,161],"most":[48],"achievements":[50],"about":[52],"single":[53,80],"language,":[54],"this":[56],"paper,":[57],"hybrid":[59,74,163,192],"method":[60,75,164,171,175],"which":[61],"integrates":[62,130],"deep":[64],"features":[66,70],"shallow":[68],"is":[71,213],"proposed.":[72],"The":[73,127,152,173],"can":[76,158,194],"not":[77],"only":[78],"realize":[79,86],"language":[81],"but":[85],"bilingual":[87],"as":[91,95,134],"well.":[92],"Models":[93],"such":[94],"recurrent":[96],"neural":[97],"networks":[98],"(RNNs)":[99],"long":[101],"short":[102],"term":[103],"memory(LSTM),":[104],"Na\u00efve":[105],"Bayes":[106],"Support":[107],"Vector":[108],"Machine":[109],"(NB-SVM),":[110],"word":[111],"vectors":[112],"bag-of-words":[114],"explored.":[116],"Firstly,":[117],"these":[118],"models":[119],"studied":[121],"separately":[122],"task.":[126,140],"paper":[128],"then":[129],"above":[132],"whole":[136],"to":[137,180],"complete":[138],"Different":[141],"combination":[142],"strategies":[143],"discussed":[145],"regarding":[146],"contribution":[148],"each":[150],"method.":[151],"experiments":[153],"show":[154],"that":[155],"accuracy":[157,204],"reach":[159],"89%":[160],"performs":[165],"much":[166],"better":[167],"than":[168],"any":[169],"other":[170],"individually.":[172],"proposed":[174],"achieves":[176],"performance":[178],"close":[179],"state-of-the-art":[182],"based":[184],"had-engineered":[187],"features.":[188],"What's":[189],"more,":[190],"model":[193],"learn":[195],"more":[196,210],"linguistic":[197],"phenomena":[198],"growth":[201],"emotional":[206],"tendency":[207],"discrimination":[208],"when":[209],"background":[211],"knowledge":[212],"available.":[214]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}