{"id":"https://openalex.org/W2795058418","doi":"https://doi.org/10.1145/3178212.3178230","title":"Combining Word Order and CNN-LSTM for Sentence Sentiment Classification","display_name":"Combining Word Order and CNN-LSTM for Sentence Sentiment Classification","publication_year":2017,"publication_date":"2017-12-28","ids":{"openalex":"https://openalex.org/W2795058418","doi":"https://doi.org/10.1145/3178212.3178230","mag":"2795058418"},"language":"en","primary_location":{"id":"doi:10.1145/3178212.3178230","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3178212.3178230","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 International Conference on Software and e-Business","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/A5012633404","display_name":"Kai Shuang","orcid":"https://orcid.org/0000-0003-0917-3541"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Kai Shuang","raw_affiliation_strings":["State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035707443","display_name":"Xintao Ren","orcid":"https://orcid.org/0000-0002-5079-4158"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xintao Ren","raw_affiliation_strings":["State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100692949","display_name":"Jian Chen","orcid":"https://orcid.org/0000-0002-2135-8752"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Chen","raw_affiliation_strings":["State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021453743","display_name":"Xiaohan Shan","orcid":"https://orcid.org/0000-0002-5538-5572"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaohan Shan","raw_affiliation_strings":["State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077532535","display_name":"Peng Xu","orcid":"https://orcid.org/0000-0003-3399-9722"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Xu","raw_affiliation_strings":["State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5012633404"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.39,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.72865305,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"17","last_page":"21"},"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":0.9997000098228455,"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/T10181","display_name":"Natural Language Processing Techniques","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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8471921682357788},{"id":"https://openalex.org/keywords/word2vec","display_name":"Word2vec","score":0.7737111449241638},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.7443176507949829},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7131234407424927},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.704943060874939},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6665198802947998},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6604410409927368},{"id":"https://openalex.org/keywords/word-embedding","display_name":"Word embedding","score":0.6343303322792053},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.6058691740036011},{"id":"https://openalex.org/keywords/word-order","display_name":"Word order","score":0.4679257869720459},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.4400532841682434},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43002790212631226},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.42614200711250305},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3745909631252289},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.11429452896118164}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8471921682357788},{"id":"https://openalex.org/C2776461190","wikidata":"https://www.wikidata.org/wiki/Q22673982","display_name":"Word2vec","level":3,"score":0.7737111449241638},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.7443176507949829},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7131234407424927},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.704943060874939},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6665198802947998},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6604410409927368},{"id":"https://openalex.org/C2777462759","wikidata":"https://www.wikidata.org/wiki/Q18395344","display_name":"Word embedding","level":3,"score":0.6343303322792053},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.6058691740036011},{"id":"https://openalex.org/C70777604","wikidata":"https://www.wikidata.org/wiki/Q257885","display_name":"Word order","level":2,"score":0.4679257869720459},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.4400532841682434},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43002790212631226},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.42614200711250305},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3745909631252289},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.11429452896118164},{"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:10.1145/3178212.3178230","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3178212.3178230","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 International Conference on Software and e-Business","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6600000262260437,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1832693441","https://openalex.org/W1904365287","https://openalex.org/W2064675550","https://openalex.org/W2070246124","https://openalex.org/W2112796928","https://openalex.org/W2119408773","https://openalex.org/W2120615054","https://openalex.org/W2125573226","https://openalex.org/W2132166724","https://openalex.org/W2141599568","https://openalex.org/W2143612262","https://openalex.org/W2146502635","https://openalex.org/W2153579005","https://openalex.org/W2158899491","https://openalex.org/W2160660844","https://openalex.org/W2251682575","https://openalex.org/W2251738400","https://openalex.org/W2618530766","https://openalex.org/W2930957955","https://openalex.org/W2950133940","https://openalex.org/W2963355447","https://openalex.org/W2997617958","https://openalex.org/W2998216295","https://openalex.org/W2998508934","https://openalex.org/W2998704965","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W3003606604","https://openalex.org/W2946409105","https://openalex.org/W3040974839","https://openalex.org/W2795129682","https://openalex.org/W3152932816","https://openalex.org/W2985392712","https://openalex.org/W4388996947","https://openalex.org/W3133567596","https://openalex.org/W2798009317","https://openalex.org/W4382201653"],"abstract_inverted_index":{"Neural":[0,18,23],"network":[1,31],"models":[2,32],"have":[3],"been":[4],"demonstrated":[5],"to":[6,70,103],"be":[7,54],"capable":[8],"of":[9,39,65,99,108],"achieving":[10],"state-of-the-art":[11],"performance":[12],"in":[13,43,50,68,114,130,143,167],"sentence":[14,69,87,109],"sentiment":[15,88,115,144,168],"classification.":[16],"Convolutional":[17],"Networks":[19,24],"(CNNs)":[20],"and":[21,101,141,149],"Recurrent":[22],"(RNNs)":[25],"are":[26],"two":[27],"widely":[28],"used":[29],"neural":[30],"for":[33,86],"NLP.":[34],"However,":[35],"since":[36],"sentences":[37],"consist":[38],"the":[40,57,63,72,97,119,139,157,160],"same":[41],"words":[42],"different":[44,48],"order":[45,67,83,107,132,162],"may":[46],"represent":[47],"meaning":[49],"sentiment,":[51],"it":[52],"cannot":[53],"neglected":[55],"that":[56,81,105,156],"word":[58,66,82,106,120,131,161],"embedding":[59,121],"training":[60,73,135],"model":[61,93,128,158],"ignores":[62],"factor":[64],"quicken":[71],"process.":[74,136],"In":[75],"this":[76],"work,":[77],"we":[78],"mainly":[79],"consider":[80],"is":[84,123],"important":[85,112],"classification,":[89],"designing":[90],"an":[91,111,126],"encode-decode":[92],"called":[94],"CNN-LSTM":[95,140],"combined":[96],"strength":[98],"CNN":[100],"LSTM":[102],"demonstrate":[104],"plays":[110],"role":[113],"analysis":[116],"based":[117],"on":[118,147],"which":[122],"designed":[124],"as":[125],"order_w2v":[127,142],"taking":[129],"during":[133],"word2vec":[134],"We":[137],"evaluate":[138],"classification":[145],"both":[146],"Chinese":[148],"English":[150],"datasets.":[151],"The":[152],"experimental":[153],"results":[154,166],"verify":[155],"considering":[159],"can":[163],"achieve":[164],"better":[165],"analysis.":[169]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"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"}
