{"id":"https://openalex.org/W7131116520","doi":"https://doi.org/10.1109/access.2026.3667314","title":"GCMA-Net: A Gated Cross-Modal Attention Network for Arabic Multimodal Sentiment Analysis","display_name":"GCMA-Net: A Gated Cross-Modal Attention Network for Arabic Multimodal Sentiment Analysis","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7131116520","doi":"https://doi.org/10.1109/access.2026.3667314"},"language":null,"primary_location":{"id":"doi:10.1109/access.2026.3667314","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3667314","pdf_url":null,"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://doi.org/10.1109/access.2026.3667314","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5120656216","display_name":"Ayoub Ben Cheikhi","orcid":null},"institutions":[{"id":"https://openalex.org/I81605866","display_name":"Sidi Mohamed Ben Abdellah University","ror":"https://ror.org/04efg9a07","country_code":"MA","type":"education","lineage":["https://openalex.org/I81605866"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Ayoub Ben Cheikhi","raw_affiliation_strings":["L3IA Laboratory, Faculty of Sciences Dhar El Mahraz, Sidi Mohamed Ben Abdellah University, Fes, Morocco"],"raw_orcid":"https://orcid.org/0009-0005-4245-5921","affiliations":[{"raw_affiliation_string":"L3IA Laboratory, Faculty of Sciences Dhar El Mahraz, Sidi Mohamed Ben Abdellah University, Fes, Morocco","institution_ids":["https://openalex.org/I81605866"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085575952","display_name":"El Habib Nfaoui","orcid":"https://orcid.org/0000-0002-5816-0897"},"institutions":[{"id":"https://openalex.org/I81605866","display_name":"Sidi Mohamed Ben Abdellah University","ror":"https://ror.org/04efg9a07","country_code":"MA","type":"education","lineage":["https://openalex.org/I81605866"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"El Habib Nfaoui","raw_affiliation_strings":["L3IA Laboratory, Faculty of Sciences Dhar El Mahraz, Sidi Mohamed Ben Abdellah University, Fes, Morocco"],"raw_orcid":"https://orcid.org/0000-0002-5816-0897","affiliations":[{"raw_affiliation_string":"L3IA Laboratory, Faculty of Sciences Dhar El Mahraz, Sidi Mohamed Ben Abdellah University, Fes, Morocco","institution_ids":["https://openalex.org/I81605866"]}]}],"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":39.1126,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.99520257,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"14","issue":null,"first_page":"30733","last_page":"30746"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.7465000152587891,"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":0.7465000152587891,"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/T10667","display_name":"Emotion and Mood Recognition","score":0.1315000057220459,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.01549999974668026,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/sentiment-analysis","display_name":"Sentiment analysis","score":0.6435999870300293},{"id":"https://openalex.org/keywords/arabic","display_name":"Arabic","score":0.620199978351593},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.6090999841690063},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.5400999784469604},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.42100000381469727},{"id":"https://openalex.org/keywords/multimodality","display_name":"Multimodality","score":0.34040001034736633}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.823199987411499},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6452000141143799},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.6435999870300293},{"id":"https://openalex.org/C96455323","wikidata":"https://www.wikidata.org/wiki/Q13955","display_name":"Arabic","level":2,"score":0.620199978351593},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.6090999841690063},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5455999970436096},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.5400999784469604},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.42100000381469727},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4120999872684479},{"id":"https://openalex.org/C2780910867","wikidata":"https://www.wikidata.org/wiki/Q1952416","display_name":"Multimodality","level":2,"score":0.34040001034736633},{"id":"https://openalex.org/C2993807640","wikidata":"https://www.wikidata.org/wiki/Q103709453","display_name":"Attention network","level":2,"score":0.3000999987125397},{"id":"https://openalex.org/C135641252","wikidata":"https://www.wikidata.org/wiki/Q738567","display_name":"Multimodal interaction","level":2,"score":0.27799999713897705},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.25859999656677246}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/access.2026.3667314","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3667314","pdf_url":null,"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"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3667314","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3667314","pdf_url":null,"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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Arabic":[0,146],"multimodal":[1,74,99,122,145],"sentiment":[2,123,153],"analysis":[3,154],"(MSA)":[4],"remains":[5],"challenging":[6],"due":[7],"to":[8,34,54,108,143,148],"linguistic":[9],"diversity,":[10],"modality":[11],"imbalance,":[12],"and":[13,41,51,58,87,103,140],"the":[14,65,80,104,114,129,141],"limitations":[15],"of":[16,90,116,131],"traditional":[17],"fusion":[18,53,100,118],"techniques":[19],"in":[20,120],"capturing":[21],"cross-modal":[22,49,137],"interactions.":[23],"This":[24],"study":[25],"proposes":[26],"GCMA-Net,":[27],"a":[28,56],"Gated":[29],"Cross-Modal":[30],"Attention":[31],"Network":[32],"designed":[33],"model":[35,45],"fine-grained":[36],"relationships":[37],"across":[38],"text,":[39],"audio,":[40],"visual":[42],"features.":[43],"The":[44,125],"employs":[46],"modality-specific":[47],"projection,":[48],"attention,":[50],"gated":[52],"generate":[55],"unified":[57],"contextually":[59],"enriched":[60],"latent":[61,133],"representation.":[62],"Experiments":[63],"on":[64],"Ar-MuSA":[66],"dataset":[67],"show":[68],"that":[69],"GCMA-Net":[70],"significantly":[71],"outperforms":[72],"existing":[73],"fusion-based":[75],"baselines":[76],"as":[77,79],"well":[78],"UniTextFusion":[81],"state-of-the-art":[82],"method,":[83],"achieving":[84],"80.17%":[85],"accuracy":[86],"an":[88],"F1-score":[89],"0.8015.The":[91],"proposed":[92],"approach":[93],"is":[94],"compared":[95],"against":[96],"widely":[97],"used":[98],"baseline":[101],"models,":[102],"improvements":[105],"are":[106],"confirmed":[107],"be":[109],"statistically":[110],"significant.These":[111],"results":[112],"demonstrate":[113],"effectiveness":[115],"interaction-centric":[117],"architectures":[119],"strengthening":[121],"prediction.":[124],"study\u2019s":[126],"implications":[127],"highlight":[128],"importance":[130],"richer":[132],"spaces,":[134],"more":[135,150],"expressive":[136],"alignment":[138],"mechanisms,":[139],"need":[142],"expand":[144],"resources":[147],"develop":[149],"robust,":[151],"generalizable":[152],"models.":[155]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-02-24T00:00:00"}