{"id":"https://openalex.org/W3016921356","doi":"https://doi.org/10.1109/access.2020.2988550","title":"Sentiment Classification Using a Single-Layered BiLSTM Model","display_name":"Sentiment Classification Using a Single-Layered BiLSTM Model","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3016921356","doi":"https://doi.org/10.1109/access.2020.2988550","mag":"3016921356"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.2988550","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2988550","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09069952.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/ielx7/6287639/8948470/09069952.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5059235837","display_name":"Zabit Hameed","orcid":"https://orcid.org/0000-0003-2514-1064"},"institutions":[{"id":"https://openalex.org/I136040515","display_name":"Universidad de Deusto","ror":"https://ror.org/00ne6sr39","country_code":"ES","type":"education","lineage":["https://openalex.org/I136040515"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Zabit Hameed","raw_affiliation_strings":["eVida Research Group, University of Deusto, Bilbao, Spain"],"affiliations":[{"raw_affiliation_string":"eVida Research Group, University of Deusto, Bilbao, Spain","institution_ids":["https://openalex.org/I136040515"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028149208","display_name":"Begonya Garc\u00eda-Zapirain","orcid":"https://orcid.org/0000-0002-9356-1186"},"institutions":[{"id":"https://openalex.org/I136040515","display_name":"Universidad de Deusto","ror":"https://ror.org/00ne6sr39","country_code":"ES","type":"education","lineage":["https://openalex.org/I136040515"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Begonya Garcia-Zapirain","raw_affiliation_strings":["eVida Research Group, University of Deusto, Bilbao, Spain"],"affiliations":[{"raw_affiliation_string":"eVida Research Group, University of Deusto, Bilbao, Spain","institution_ids":["https://openalex.org/I136040515"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5059235837"],"corresponding_institution_ids":["https://openalex.org/I136040515"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":17.5624,"has_fulltext":true,"cited_by_count":254,"citation_normalized_percentile":{"value":0.99383666,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"8","issue":null,"first_page":"73992","last_page":"74001"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":1.0,"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":1.0,"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":0.9980999827384949,"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/T11644","display_name":"Spam and Phishing Detection","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.8484175801277161},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.774895966053009},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.7307449579238892},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6345286965370178},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.57981938123703},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.5618941187858582},{"id":"https://openalex.org/keywords/polarity","display_name":"Polarity (international relations)","score":0.49085766077041626},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.4740866422653198},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4515582025051117},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.433987557888031},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.41926848888397217},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41509541869163513},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4148532450199127},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3683072030544281}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8484175801277161},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.774895966053009},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.7307449579238892},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6345286965370178},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.57981938123703},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.5618941187858582},{"id":"https://openalex.org/C2777361361","wikidata":"https://www.wikidata.org/wiki/Q1112585","display_name":"Polarity (international relations)","level":3,"score":0.49085766077041626},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.4740866422653198},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4515582025051117},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.433987557888031},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.41926848888397217},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41509541869163513},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4148532450199127},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3683072030544281},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C1491633281","wikidata":"https://www.wikidata.org/wiki/Q7868","display_name":"Cell","level":2,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/access.2020.2988550","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2988550","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09069952.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:deustoteka.deusto.es:20.500.14454/1868","is_oa":true,"landing_page_url":"https://hdl.handle.net/20.500.14454/1868","pdf_url":"https://deustoteka.deusto.es/bitstreams/301f885d-07b1-4f77-ada7-dfd4a5076f2c/download","source":{"id":"https://openalex.org/S7407055256","display_name":"DeustoTeka","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-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:doaj.org/article:89858ddc034849d694f9549877a5ce03","is_oa":true,"landing_page_url":"https://doaj.org/article/89858ddc034849d694f9549877a5ce03","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"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 8, Pp 73992-74001 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.2988550","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2988550","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09069952.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":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3016921356.pdf","grobid_xml":"https://content.openalex.org/works/W3016921356.grobid-xml"},"referenced_works_count":45,"referenced_works":["https://openalex.org/W1614298861","https://openalex.org/W1832693441","https://openalex.org/W1889268436","https://openalex.org/W2012070465","https://openalex.org/W2034090215","https://openalex.org/W2047756776","https://openalex.org/W2064675550","https://openalex.org/W2095705004","https://openalex.org/W2113459411","https://openalex.org/W2118020653","https://openalex.org/W2131774270","https://openalex.org/W2143017621","https://openalex.org/W2154359981","https://openalex.org/W2163455955","https://openalex.org/W2166706824","https://openalex.org/W2250539671","https://openalex.org/W2251381233","https://openalex.org/W2251939518","https://openalex.org/W2278629362","https://openalex.org/W2306706380","https://openalex.org/W2513263213","https://openalex.org/W2548006041","https://openalex.org/W2562607067","https://openalex.org/W2757442264","https://openalex.org/W2770736169","https://openalex.org/W2801716390","https://openalex.org/W2899329739","https://openalex.org/W2901078833","https://openalex.org/W2923528470","https://openalex.org/W2941799245","https://openalex.org/W2959988970","https://openalex.org/W2963023579","https://openalex.org/W2963042536","https://openalex.org/W2964236337","https://openalex.org/W2964319599","https://openalex.org/W2972615427","https://openalex.org/W2972830289","https://openalex.org/W4210984920","https://openalex.org/W6636510571","https://openalex.org/W6639364127","https://openalex.org/W6674330103","https://openalex.org/W6676984168","https://openalex.org/W6682839988","https://openalex.org/W6691459498","https://openalex.org/W6691501495"],"related_works":["https://openalex.org/W2953234277","https://openalex.org/W2626256601","https://openalex.org/W2900413183","https://openalex.org/W147410782","https://openalex.org/W3022252430","https://openalex.org/W3103989898","https://openalex.org/W4287804464","https://openalex.org/W803346624","https://openalex.org/W2152352598","https://openalex.org/W1984947604"],"abstract_inverted_index":{"This":[0],"study":[1],"presents":[2],"a":[3,57],"computationally":[4,110],"efficient":[5,111],"deep":[6],"learning":[7],"model":[8],"for":[9,116],"binary":[10],"sentiment":[11,18,123],"classification,":[12],"which":[13],"aims":[14],"to":[15],"decide":[16],"the":[17,80,90,103,120],"polarity":[19],"of":[20,65,83,122],"people's":[21],"opinions,":[22],"attitudes,":[23],"and":[24,61,68,73,112],"emotions":[25],"expressed":[26],"in":[27,119],"written":[28],"text.":[29],"To":[30],"achieve":[31],"this,":[32],"we":[33],"exploited":[34],"three":[35],"widely":[36],"practiced":[37],"datasets":[38],"based":[39,107],"on":[40,70],"public":[41],"opinions":[42],"about":[43],"movies.":[44],"We":[45,77],"utilized":[46],"merely":[47],"one":[48],"bidirectional":[49],"long":[50],"short-term":[51],"memory":[52],"(BiLSTM)":[53],"layer":[54],"along":[55],"with":[56,89],"global":[58],"pooling":[59],"mechanism":[60],"achieved":[62],"an":[63],"accuracy":[64],"80.500%,":[66],"85.780%,":[67],"90.585%":[69],"MR,":[71],"SST2":[72],"IMDb":[74],"datasets,":[75],"respectively.":[76],"concluded":[78],"that":[79,102],"performance":[81],"metrics":[82],"our":[84],"proposed":[85,104],"approach":[86],"are":[87],"competitive":[88],"recently":[91],"published":[92],"models,":[93],"having":[94],"comparatively":[95],"complex":[96],"architectures.":[97],"Also,":[98],"it":[99],"is":[100,109],"inferred":[101],"single-layered":[105],"BiLSTM":[106],"architecture":[108],"can":[113],"be":[114],"recommended":[115],"real-time":[117],"applications":[118],"field":[121],"analysis.":[124]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":59},{"year":2024,"cited_by_count":59},{"year":2023,"cited_by_count":54},{"year":2022,"cited_by_count":36},{"year":2021,"cited_by_count":34},{"year":2020,"cited_by_count":4}],"updated_date":"2026-03-26T15:22:09.906841","created_date":"2025-10-10T00:00:00"}