{"id":"https://openalex.org/W4402982786","doi":"https://doi.org/10.1109/icme57554.2024.10687630","title":"Sentiment Confidence Separation: A Trust-Optimized Framework for Multimodal Sentiment Classification","display_name":"Sentiment Confidence Separation: A Trust-Optimized Framework for Multimodal Sentiment Classification","publication_year":2024,"publication_date":"2024-07-15","ids":{"openalex":"https://openalex.org/W4402982786","doi":"https://doi.org/10.1109/icme57554.2024.10687630"},"language":"en","primary_location":{"id":"doi:10.1109/icme57554.2024.10687630","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icme57554.2024.10687630","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Multimedia and Expo (ICME)","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/A5018346785","display_name":"Zemin Tang","orcid":"https://orcid.org/0000-0002-8171-3234"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zemin Tang","raw_affiliation_strings":["Hunan University,College of Computer Science and Electronic Engineering,Changsha,China"],"affiliations":[{"raw_affiliation_string":"Hunan University,College of Computer Science and Electronic Engineering,Changsha,China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101988330","display_name":"Min Shi","orcid":"https://orcid.org/0009-0003-0238-6306"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Shi","raw_affiliation_strings":["Hunan University,College of Computer Science and Electronic Engineering,Changsha,China"],"affiliations":[{"raw_affiliation_string":"Hunan University,College of Computer Science and Electronic Engineering,Changsha,China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017557124","display_name":"Zhibang Yang","orcid":"https://orcid.org/0009-0005-1523-5253"},"institutions":[{"id":"https://openalex.org/I198357462","display_name":"Changsha University","ror":"https://ror.org/011d8sm39","country_code":"CN","type":"education","lineage":["https://openalex.org/I198357462"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhibang Yang","raw_affiliation_strings":["Changsha University,Hunan Province Key Laboratory of Industrial Internet Technology and Security,Changsha,China"],"affiliations":[{"raw_affiliation_string":"Changsha University,Hunan Province Key Laboratory of Industrial Internet Technology and Security,Changsha,China","institution_ids":["https://openalex.org/I198357462"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018453698","display_name":"Xu Zhou","orcid":"https://orcid.org/0000-0002-0764-0620"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Zhou","raw_affiliation_strings":["Hunan University,College of Computer Science and Electronic Engineering,Changsha,China"],"affiliations":[{"raw_affiliation_string":"Hunan University,College of Computer Science and Electronic Engineering,Changsha,China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100622590","display_name":"Cen Chen","orcid":"https://orcid.org/0000-0003-1389-0148"},"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":"Cen Chen","raw_affiliation_strings":["South China University of Technology,School of Future Technology,Guangzhou,China"],"affiliations":[{"raw_affiliation_string":"South China University of Technology,School of Future Technology,Guangzhou,China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045125183","display_name":"Joey Tianyi Zhou","orcid":"https://orcid.org/0000-0002-4675-7055"},"institutions":[{"id":"https://openalex.org/I115228651","display_name":"Agency for Science, Technology and Research","ror":"https://ror.org/036wvzt09","country_code":"SG","type":"government","lineage":["https://openalex.org/I115228651"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Joey Tianyi Zhou","raw_affiliation_strings":["Agency for Science, Technology and Research,Centre for Frontier AI Research,Singapore"],"affiliations":[{"raw_affiliation_string":"Agency for Science, Technology and Research,Centre for Frontier AI Research,Singapore","institution_ids":["https://openalex.org/I115228651"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5018346785"],"corresponding_institution_ids":["https://openalex.org/I16609230"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14165532,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"32","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9332000017166138,"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":0.9332000017166138,"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/sentiment-analysis","display_name":"Sentiment analysis","score":0.7566247582435608},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6864063739776611},{"id":"https://openalex.org/keywords/separation","display_name":"Separation (statistics)","score":0.5652649998664856},{"id":"https://openalex.org/keywords/consumer-confidence-index","display_name":"Consumer confidence index","score":0.5532130002975464},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5246382355690002},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3906059265136719},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.24483507871627808},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.0734964907169342}],"concepts":[{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.7566247582435608},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6864063739776611},{"id":"https://openalex.org/C2776061190","wikidata":"https://www.wikidata.org/wiki/Q7451805","display_name":"Separation (statistics)","level":2,"score":0.5652649998664856},{"id":"https://openalex.org/C96405632","wikidata":"https://www.wikidata.org/wiki/Q1128416","display_name":"Consumer confidence index","level":2,"score":0.5532130002975464},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5246382355690002},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3906059265136719},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.24483507871627808},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0734964907169342},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme57554.2024.10687630","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icme57554.2024.10687630","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322843","display_name":"Natural Science Foundation of\u00a0Hunan Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W2556418146","https://openalex.org/W2883409523","https://openalex.org/W3011221694","https://openalex.org/W3014050130","https://openalex.org/W3033615934","https://openalex.org/W3093400813","https://openalex.org/W3206201541","https://openalex.org/W4293517975","https://openalex.org/W4297499129","https://openalex.org/W4309769112","https://openalex.org/W4312808544","https://openalex.org/W4313066313","https://openalex.org/W4322096735","https://openalex.org/W4322736091","https://openalex.org/W4376109777","https://openalex.org/W4385349476","https://openalex.org/W6726983090","https://openalex.org/W6755207826","https://openalex.org/W6758508654","https://openalex.org/W6780663757","https://openalex.org/W6783600611","https://openalex.org/W6796913975","https://openalex.org/W6802205604","https://openalex.org/W6839017374","https://openalex.org/W6862177750"],"related_works":["https://openalex.org/W2577390582","https://openalex.org/W2184490841","https://openalex.org/W3183992040","https://openalex.org/W4225380647","https://openalex.org/W2548633793","https://openalex.org/W3013279174","https://openalex.org/W2941935829","https://openalex.org/W3015630531","https://openalex.org/W2596247554","https://openalex.org/W3204019825"],"abstract_inverted_index":{"The":[0,28],"Multimodal":[1],"Sentiment":[2,85],"Classification":[3],"(MSC)":[4],"task":[5],"aims":[6],"to":[7],"discern":[8],"sentiments":[9],"from":[10],"diverse":[11],"data":[12],"sources.":[13],"Existing":[14],"efforts":[15],"focus":[16],"on":[17,66],"integrating":[18],"multimodal":[19],"features":[20],"and":[21,100,112,119],"enhancing":[22],"representation":[23],"learning":[24],"for":[25,40],"improved":[26],"recognition.":[27],"widespread":[29],"use":[30],"of":[31,55,127],"MSC,":[32],"particularly":[33],"in":[34,43,75,93],"risk-associated":[35],"domains,":[36],"highlights":[37],"the":[38,57,72,98,125,128],"need":[39],"heightened":[41],"trustworthiness":[42],"predictions.":[44,76,121],"However,":[45],"most":[46],"current":[47],"MSC":[48,94],"models":[49,95],"often":[50],"provide":[51],"elevated":[52],"confidence":[53,69,82],"regardless":[54],"whether":[56,67],"prediction":[58],"is":[59],"correct":[60,99],"or":[61],"not,":[62],"with":[63],"less":[64],"emphasis":[65],"this":[68],"reasonably":[70],"reflects":[71],"model\u2019s":[73],"certainty":[74],"This":[77],"paper":[78],"proposes":[79],"a":[80],"novel":[81],"optimization":[83],"framework,":[84],"Confidence":[86,108],"Separation":[87,109,114],"(SCS),":[88],"which":[89],"helps":[90],"address":[91],"unreliability":[92],"by":[96],"making":[97],"incorrect":[101],"predictions":[102],"output":[103],"discriminative":[104],"confidences.":[105],"SCS":[106],"comprises":[107],"Loss":[110],"(CSL)":[111],"Flatness-Based":[113],"Optimization":[115],"(FBSO),":[116],"facilitating":[117],"reliable":[118],"precise":[120],"Comprehensive":[122],"experimentation":[123],"validates":[124],"efficacy":[126],"proposed":[129],"approach":[130],"across":[131],"multiple":[132],"mainstream":[133],"datasets.":[134]},"counts_by_year":[],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}
