{"id":"https://openalex.org/W2972830289","doi":"https://doi.org/10.1109/access.2019.2940051","title":"Deep Learning Based Weighted Feature Fusion Approach for Sentiment Analysis","display_name":"Deep Learning Based Weighted Feature Fusion Approach for Sentiment Analysis","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2972830289","doi":"https://doi.org/10.1109/access.2019.2940051","mag":"2972830289"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2940051","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2940051","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08827512.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/ielx7/6287639/8600701/08827512.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076070005","display_name":"Mohd Usama","orcid":"https://orcid.org/0000-0001-6524-7694"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mohd Usama","raw_affiliation_strings":["Embedded and Pervasive Computing (EPIC) Laboratory, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Embedded and Pervasive Computing (EPIC) Laboratory, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045486208","display_name":"Wenjing Xiao","orcid":"https://orcid.org/0000-0002-8231-2467"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenjing Xiao","raw_affiliation_strings":["Embedded and Pervasive Computing (EPIC) Laboratory, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-8231-2467","affiliations":[{"raw_affiliation_string":"Embedded and Pervasive Computing (EPIC) Laboratory, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100715165","display_name":"Belal Ahmad","orcid":"https://orcid.org/0000-0001-5917-0029"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Belal Ahmad","raw_affiliation_strings":["Embedded and Pervasive Computing (EPIC) Laboratory, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Embedded and Pervasive Computing (EPIC) Laboratory, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001398914","display_name":"Jiafu Wan","orcid":"https://orcid.org/0000-0001-9188-4179"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiafu Wan","raw_affiliation_strings":["Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085933596","display_name":"Mohammad Mehedi Hassan","orcid":"https://orcid.org/0000-0002-3479-3606"},"institutions":[{"id":"https://openalex.org/I28022161","display_name":"King Saud University","ror":"https://ror.org/02f81g417","country_code":"SA","type":"education","lineage":["https://openalex.org/I28022161"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Mohammad Mehedi Hassan","raw_affiliation_strings":["College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia"],"raw_orcid":"https://orcid.org/0000-0002-3479-3606","affiliations":[{"raw_affiliation_string":"College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia","institution_ids":["https://openalex.org/I28022161"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080966304","display_name":"Abdulhameed Alelaiwi","orcid":"https://orcid.org/0000-0003-4442-8378"},"institutions":[{"id":"https://openalex.org/I28022161","display_name":"King Saud University","ror":"https://ror.org/02f81g417","country_code":"SA","type":"education","lineage":["https://openalex.org/I28022161"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Abdulhameed Alelaiwi","raw_affiliation_strings":["College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia"],"raw_orcid":"https://orcid.org/0000-0003-4442-8378","affiliations":[{"raw_affiliation_string":"College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia","institution_ids":["https://openalex.org/I28022161"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"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":2.5398,"has_fulltext":true,"cited_by_count":29,"citation_normalized_percentile":{"value":0.91557117,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"7","issue":null,"first_page":"140252","last_page":"140260"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9991999864578247,"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":0.9991999864578247,"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":0.9955000281333923,"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":0.9939000010490417,"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":0.8202481269836426},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6836757063865662},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5665966272354126},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5479618310928345},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5446661114692688},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5310806632041931},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5067151188850403},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.5013887882232666},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5002486705780029},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44522398710250854},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.4400281310081482},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4301665425300598},{"id":"https://openalex.org/keywords/information-fusion","display_name":"Information fusion","score":0.41039833426475525},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3288160562515259}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8202481269836426},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6836757063865662},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5665966272354126},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5479618310928345},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5446661114692688},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5310806632041931},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5067151188850403},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.5013887882232666},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5002486705780029},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44522398710250854},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.4400281310081482},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4301665425300598},{"id":"https://openalex.org/C2982962833","wikidata":"https://www.wikidata.org/wiki/Q17092450","display_name":"Information fusion","level":2,"score":0.41039833426475525},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3288160562515259},{"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},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2019.2940051","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2940051","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08827512.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:9e821cf3bab14046ae3774e05ae83936","is_oa":true,"landing_page_url":"https://doaj.org/article/9e821cf3bab14046ae3774e05ae83936","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 140252-140260 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2940051","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2940051","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08827512.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":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.800000011920929}],"awards":[{"id":"https://openalex.org/G797454101","display_name":null,"funder_award_id":"RSP\u20102019","funder_id":"https://openalex.org/F4320321145","funder_display_name":"King Saud University"},{"id":"https://openalex.org/G8953071891","display_name":null,"funder_award_id":"RSP-2019/18","funder_id":"https://openalex.org/F4320321145","funder_display_name":"King Saud University"}],"funders":[{"id":"https://openalex.org/F4320321145","display_name":"King Saud University","ror":"https://ror.org/02f81g417"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2972830289.pdf","grobid_xml":"https://content.openalex.org/works/W2972830289.grobid-xml"},"referenced_works_count":54,"referenced_works":["https://openalex.org/W6908809","https://openalex.org/W71795751","https://openalex.org/W1816079941","https://openalex.org/W1832693441","https://openalex.org/W1889268436","https://openalex.org/W2012070465","https://openalex.org/W2064675550","https://openalex.org/W2111369166","https://openalex.org/W2119408773","https://openalex.org/W2125573226","https://openalex.org/W2132166724","https://openalex.org/W2143612262","https://openalex.org/W2154359981","https://openalex.org/W2163455955","https://openalex.org/W2163605009","https://openalex.org/W2166706824","https://openalex.org/W2250644439","https://openalex.org/W2250966211","https://openalex.org/W2251939518","https://openalex.org/W2468438421","https://openalex.org/W2470673105","https://openalex.org/W2599261605","https://openalex.org/W2606698885","https://openalex.org/W2610135452","https://openalex.org/W2624775096","https://openalex.org/W2786411768","https://openalex.org/W2795613961","https://openalex.org/W2796802878","https://openalex.org/W2892172277","https://openalex.org/W2894178883","https://openalex.org/W2899792733","https://openalex.org/W2951559648","https://openalex.org/W2962785888","https://openalex.org/W2963083845","https://openalex.org/W2963355447","https://openalex.org/W2963889363","https://openalex.org/W2963974064","https://openalex.org/W2964199361","https://openalex.org/W2966935339","https://openalex.org/W2970213520","https://openalex.org/W6600284362","https://openalex.org/W6601425427","https://openalex.org/W6602989467","https://openalex.org/W6639364127","https://openalex.org/W6640598943","https://openalex.org/W6676557066","https://openalex.org/W6678114183","https://openalex.org/W6678656546","https://openalex.org/W6679879607","https://openalex.org/W6682839988","https://openalex.org/W6684191040","https://openalex.org/W6691459498","https://openalex.org/W6734978023","https://openalex.org/W6764305895"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W2731899572","https://openalex.org/W4230611425","https://openalex.org/W4294635752","https://openalex.org/W4304166257","https://openalex.org/W4383066092","https://openalex.org/W2355579697","https://openalex.org/W4360871138","https://openalex.org/W3208972923"],"abstract_inverted_index":{"Deep":[0],"learning":[1],"algorithms":[2],"have":[3,72],"achieved":[4],"remarkable":[5],"results":[6,130],"in":[7,82,86],"the":[8,45,49,64,95,118,133],"natural":[9],"language":[10],"processing(NLP)":[11],"and":[12,28,66,76,99,121,139,155,160],"computer":[13],"vision.":[14],"Hence,":[15],"a":[16],"trend":[17],"still":[18],"going":[19],"on":[20,137,157],"to":[21,36,60,69,93],"use":[22,90],"these":[23,52],"algorithms,":[24],"such":[25],"as":[26,102,104],"convolution":[27],"recurrent":[29],"neural":[30,109],"networks,":[31],"for":[32],"text":[33],"analytic":[34],"task":[35],"extract":[37],"useful":[38],"information.":[39],"Features":[40],"extraction":[41],"is":[42],"one":[43,58,67],"of":[44,51,97,117,152],"important":[46],"reasons":[47],"behind":[48],"success":[50],"networks.":[53,110],"Moreover":[54],"passing":[55],"features":[56,78,106,112,123,142],"from":[57,107,114,125],"layer":[59,62],"another":[61,70],"within":[63],"network":[65,68,71,127],"done.":[73],"However":[74],"multilevel":[75,101,138],"multitype":[77,105,122,140],"fusion":[79,143],"remains":[80],"unexplored":[81],"sentiment":[83],"analysis.":[84],"So,":[85],"this":[87],"paper,":[88],"we":[89],"three":[91],"datasets":[92,162],"display":[94],"advantages":[96],"extracting":[98],"fusing":[100],"well":[103],"different":[108,115,126],"Multilevel":[111],"are":[113,124],"layers":[116],"same":[119],"network,":[120],"architectures.":[128],"Experiment":[129],"demonstrate":[131],"that":[132],"proposed":[134],"model":[135],"based":[136],"weighted":[141],"outperforms":[144],"than":[145],"many":[146],"exiting":[147],"works":[148],"with":[149],"an":[150],"accuracy":[151],"80.2%,":[153],"48.2%,":[154],"87.0%":[156],"MR,":[158],"SST1,":[159],"SST2":[161],"respectively.":[163]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}