{"id":"https://openalex.org/W2973946059","doi":"https://doi.org/10.1109/access.2019.2942614","title":"Sentiment Analysis of Text Based on Bidirectional LSTM With Multi-Head Attention","display_name":"Sentiment Analysis of Text Based on Bidirectional LSTM With Multi-Head Attention","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2973946059","doi":"https://doi.org/10.1109/access.2019.2942614","mag":"2973946059"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2942614","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2942614","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08845615.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08845615.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100759514","display_name":"Fei Long","orcid":"https://orcid.org/0000-0001-8835-8397"},"institutions":[{"id":"https://openalex.org/I178232147","display_name":"Guizhou University","ror":"https://ror.org/02wmsc916","country_code":"CN","type":"education","lineage":["https://openalex.org/I178232147"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Long","raw_affiliation_strings":["College of Big Data and Information Engineering, Guizhou University, Guiyang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Big Data and Information Engineering, Guizhou University, Guiyang, China","institution_ids":["https://openalex.org/I178232147"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009856292","display_name":"Kai Zhou","orcid":"https://orcid.org/0000-0003-2201-6065"},"institutions":[{"id":"https://openalex.org/I178232147","display_name":"Guizhou University","ror":"https://ror.org/02wmsc916","country_code":"CN","type":"education","lineage":["https://openalex.org/I178232147"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Zhou","raw_affiliation_strings":["College of Big Data and Information Engineering, Guizhou University, Guiyang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Big Data and Information Engineering, Guizhou University, Guiyang, China","institution_ids":["https://openalex.org/I178232147"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028245257","display_name":"Weihua Ou","orcid":"https://orcid.org/0000-0001-5241-7703"},"institutions":[{"id":"https://openalex.org/I154893126","display_name":"Guizhou Normal University","ror":"https://ror.org/02x1pa065","country_code":"CN","type":"education","lineage":["https://openalex.org/I154893126"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weihua Ou","raw_affiliation_strings":["School of Big Data and Computer Science, Guizhou Normal University, Guiyang, China"],"raw_orcid":"https://orcid.org/0000-0001-5241-7703","affiliations":[{"raw_affiliation_string":"School of Big Data and Computer Science, Guizhou Normal University, Guiyang, China","institution_ids":["https://openalex.org/I154893126"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":7.9066,"has_fulltext":true,"cited_by_count":127,"citation_normalized_percentile":{"value":0.97850727,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"7","issue":null,"first_page":"141960","last_page":"141969"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","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/T10028","display_name":"Topic Modeling","score":0.9984999895095825,"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":0.9983000159263611,"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":0.7874116897583008},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.7052181363105774},{"id":"https://openalex.org/keywords/head","display_name":"Head (geology)","score":0.6427944898605347},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5632834434509277},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.556221604347229},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3752706050872803},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.06355401873588562}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7874116897583008},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.7052181363105774},{"id":"https://openalex.org/C2780312720","wikidata":"https://www.wikidata.org/wiki/Q5689100","display_name":"Head (geology)","level":2,"score":0.6427944898605347},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5632834434509277},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.556221604347229},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3752706050872803},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.06355401873588562},{"id":"https://openalex.org/C114793014","wikidata":"https://www.wikidata.org/wiki/Q52109","display_name":"Geomorphology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2019.2942614","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2942614","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08845615.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:d68aac98966b4683a81d54d7e61fcd34","is_oa":true,"landing_page_url":"https://doaj.org/article/d68aac98966b4683a81d54d7e61fcd34","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 7, Pp 141960-141969 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2942614","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2942614","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08845615.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6899999976158142,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G4363603836","display_name":"\u9762\u5411\u4eba\u8138\u89c6\u9891\u7684\u5fc3\u7387\u4f30\u8ba1\u5173\u952e\u95ee\u9898\u7814\u7a76","funder_award_id":"61962010","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5519293298","display_name":"\u57fa\u4e8e\u7ed3\u6784\u7ea6\u675f\u7684\u8de8\u6a21\u6001\u68c0\u7d22\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61762021","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G842610578","display_name":null,"funder_award_id":"61863006","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W142730124","https://openalex.org/W1614298861","https://openalex.org/W1832693441","https://openalex.org/W2005708641","https://openalex.org/W2061436640","https://openalex.org/W2095705004","https://openalex.org/W2130942839","https://openalex.org/W2167660864","https://openalex.org/W2170240176","https://openalex.org/W2250539671","https://openalex.org/W2350902750","https://openalex.org/W2415204069","https://openalex.org/W2470673105","https://openalex.org/W2562607067","https://openalex.org/W2562781711","https://openalex.org/W2624147939","https://openalex.org/W2800452261","https://openalex.org/W2919115771","https://openalex.org/W2949847915","https://openalex.org/W2998704965","https://openalex.org/W4211186029","https://openalex.org/W4294170691","https://openalex.org/W4385245566","https://openalex.org/W6605727216","https://openalex.org/W6636510571","https://openalex.org/W6638444622","https://openalex.org/W6674330103","https://openalex.org/W6679436768","https://openalex.org/W6680532216","https://openalex.org/W6682691769","https://openalex.org/W6685053522","https://openalex.org/W6715743342","https://openalex.org/W6732958910","https://openalex.org/W6739901393"],"related_works":["https://openalex.org/W2548633793","https://openalex.org/W3013279174","https://openalex.org/W2941935829","https://openalex.org/W2596247554","https://openalex.org/W3132372214","https://openalex.org/W4224284088","https://openalex.org/W4286571989","https://openalex.org/W2765903680","https://openalex.org/W4317653575","https://openalex.org/W3204019825"],"abstract_inverted_index":{"Recent":[0],"years,":[1],"many":[2],"scientists":[3],"address":[4],"the":[5,16,30,63,89,106,114,118,122,125,130,143,151,158,163,170],"research":[6],"on":[7],"text":[8,33,70,153],"sentiment":[9,64],"analysis":[10,65],"of":[11,19,66,91,117,157],"social":[12,20,31,67],"media":[13,32,68],"due":[14],"to":[15,38,61,87,121,146,150],"exponential":[17],"growth":[18],"multimedia":[21],"content.":[22],"Natural":[23],"language":[24],"ambiguities":[25],"and":[26,55],"indirect":[27],"sentiments":[28],"within":[29],"have":[34],"made":[35],"it":[36],"hard":[37],"classify":[39],"by":[40,71,138],"using":[41,139],"traditional":[42,98],"machine":[43,99],"learning":[44],"approaches,":[45],"such":[46],"as":[47],"support":[48],"vector":[49],"machines,":[50],"naive":[51],"Bayes,":[52],"hybrid":[53],"models":[54],"so":[56],"on.":[57],"This":[58],"article":[59],"aims":[60],"investigate":[62],"Chinese":[69],"combining":[72],"Bidirectional":[73],"Long-Short":[74],"Term":[75],"Memory":[76],"(BiLSTM)":[77],"networks":[78],"with":[79,97],"a":[80,134],"Multi-head":[81],"Attention":[82],"(MHAT)":[83],"mechanism":[84,127],"in":[85],"order":[86],"overcome":[88],"deficiency":[90],"Sentiment":[92],"Analysis":[93],"that":[94,124,162],"is":[95,145],"performed":[96],"learning.":[100],"BiLSTM":[101],"networks,":[102],"not":[103],"only":[104],"solve":[105],"long-term":[107],"dependency":[108],"problem,":[109],"but":[110],"they":[111],"also":[112],"capture":[113],"actual":[115],"context":[116],"text.":[119],"Due":[120],"fact":[123],"MHAT":[126],"can":[128],"learn":[129],"relevant":[131],"information":[132],"from":[133],"different":[135],"representation":[136],"subspace":[137],"multiple":[140],"distributed":[141],"calculations,":[142],"purpose":[144],"add":[147],"influence":[148],"weights":[149],"constructed":[152],"sequence.":[154],"The":[155],"results":[156],"numerical":[159],"experiments":[160],"show":[161],"proposed":[164],"model":[165],"achieves":[166],"better":[167],"performance":[168],"than":[169],"existing":[171],"well-established":[172],"methods.":[173]},"counts_by_year":[{"year":2026,"cited_by_count":13},{"year":2025,"cited_by_count":18},{"year":2024,"cited_by_count":25},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":36},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":1}],"updated_date":"2026-05-19T21:40:30.786675","created_date":"2025-10-10T00:00:00"}
