{"id":"https://openalex.org/W7134196643","doi":"https://doi.org/10.1111/exsy.70216","title":"Multimodal Deep Learning for Online Review Helpfulness Prediction","display_name":"Multimodal Deep Learning for Online Review Helpfulness Prediction","publication_year":2026,"publication_date":"2026-02-24","ids":{"openalex":"https://openalex.org/W7134196643","doi":"https://doi.org/10.1111/exsy.70216"},"language":"en","primary_location":{"id":"doi:10.1111/exsy.70216","is_oa":false,"landing_page_url":"https://doi.org/10.1111/exsy.70216","pdf_url":null,"source":{"id":"https://openalex.org/S72232612","display_name":"Expert Systems","issn_l":"0266-4720","issn":["0266-4720","1468-0394"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Expert Systems","raw_type":"journal-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/A5108253562","display_name":"Xiaodong Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I4210096899","display_name":"Jiangsu University of Science and Technology","ror":"https://ror.org/00tyjp878","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210096899"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaodong Xie","raw_affiliation_strings":["School of Economics and Management Jiangsu University of Science and Technology  Zhenjiang China"],"raw_orcid":"https://orcid.org/0009-0006-0955-5450","affiliations":[{"raw_affiliation_string":"School of Economics and Management Jiangsu University of Science and Technology  Zhenjiang China","institution_ids":["https://openalex.org/I4210096899"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128345474","display_name":"Jie Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210096899","display_name":"Jiangsu University of Science and Technology","ror":"https://ror.org/00tyjp878","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210096899"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jie Wu","raw_affiliation_strings":["School of Economics and Management Jiangsu University of Science and Technology  Zhenjiang China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Economics and Management Jiangsu University of Science and Technology  Zhenjiang China","institution_ids":["https://openalex.org/I4210096899"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jianting Tang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210096899","display_name":"Jiangsu University of Science and Technology","ror":"https://ror.org/00tyjp878","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210096899"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianting Tang","raw_affiliation_strings":["School of Economics and Management Jiangsu University of Science and Technology  Zhenjiang China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Economics and Management Jiangsu University of Science and Technology  Zhenjiang China","institution_ids":["https://openalex.org/I4210096899"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5128347552","display_name":"Yongxiang Sheng","orcid":null},"institutions":[{"id":"https://openalex.org/I4210096899","display_name":"Jiangsu University of Science and Technology","ror":"https://ror.org/00tyjp878","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210096899"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongxiang Sheng","raw_affiliation_strings":["School of Economics and Management Jiangsu University of Science and Technology  Zhenjiang China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Economics and Management Jiangsu University of Science and Technology  Zhenjiang China","institution_ids":["https://openalex.org/I4210096899"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5128345474"],"corresponding_institution_ids":["https://openalex.org/I4210096899"],"apc_list":{"value":3860,"currency":"USD","value_usd":3860},"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.37293756,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"43","issue":"4","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11644","display_name":"Spam and Phishing Detection","score":0.24289999902248383,"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"}},"topics":[{"id":"https://openalex.org/T11644","display_name":"Spam and Phishing Detection","score":0.24289999902248383,"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"}},{"id":"https://openalex.org/T10609","display_name":"Digital Marketing and Social Media","score":0.17800000309944153,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.16910000145435333,"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/helpfulness","display_name":"Helpfulness","score":0.8672999739646912},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7060999870300293},{"id":"https://openalex.org/keywords/metadata","display_name":"Metadata","score":0.6360999941825867},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.5860999822616577},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5454000234603882},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.5336999893188477},{"id":"https://openalex.org/keywords/multimodality","display_name":"Multimodality","score":0.48969998955726624},{"id":"https://openalex.org/keywords/multimodal-learning","display_name":"Multimodal learning","score":0.4867999851703644}],"concepts":[{"id":"https://openalex.org/C2781265381","wikidata":"https://www.wikidata.org/wiki/Q5710255","display_name":"Helpfulness","level":2,"score":0.8672999739646912},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8450000286102295},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7192999720573425},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7060999870300293},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.6360999941825867},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.5860999822616577},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5587999820709229},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5454000234603882},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.5336999893188477},{"id":"https://openalex.org/C2780910867","wikidata":"https://www.wikidata.org/wiki/Q1952416","display_name":"Multimodality","level":2,"score":0.48969998955726624},{"id":"https://openalex.org/C2780660688","wikidata":"https://www.wikidata.org/wiki/Q25052564","display_name":"Multimodal learning","level":2,"score":0.4867999851703644},{"id":"https://openalex.org/C186625053","wikidata":"https://www.wikidata.org/wiki/Q1130191","display_name":"Information overload","level":2,"score":0.3361999988555908},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.32820001244544983},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.29089999198913574},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2890999913215637},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.2833000123500824},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.2705000042915344},{"id":"https://openalex.org/C97385483","wikidata":"https://www.wikidata.org/wiki/Q16954980","display_name":"Deep belief network","level":3,"score":0.2599000036716461},{"id":"https://openalex.org/C8521452","wikidata":"https://www.wikidata.org/wiki/Q203790","display_name":"Connectionism","level":3,"score":0.2590999901294708},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.257099986076355},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.25609999895095825}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1111/exsy.70216","is_oa":false,"landing_page_url":"https://doi.org/10.1111/exsy.70216","pdf_url":null,"source":{"id":"https://openalex.org/S72232612","display_name":"Expert Systems","issn_l":"0266-4720","issn":["0266-4720","1468-0394"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Expert Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.653153657913208,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G1838594565","display_name":null,"funder_award_id":"72171122","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":55,"referenced_works":["https://openalex.org/W1064650781","https://openalex.org/W1829713583","https://openalex.org/W1965449946","https://openalex.org/W1966503997","https://openalex.org/W1967025894","https://openalex.org/W2019983800","https://openalex.org/W2075964046","https://openalex.org/W2115016638","https://openalex.org/W2119821739","https://openalex.org/W2120615054","https://openalex.org/W2194775991","https://openalex.org/W2275869402","https://openalex.org/W2509632655","https://openalex.org/W2556726043","https://openalex.org/W2586885238","https://openalex.org/W2601994823","https://openalex.org/W2609010594","https://openalex.org/W2619383789","https://openalex.org/W2762700563","https://openalex.org/W2780946198","https://openalex.org/W2793787528","https://openalex.org/W2897736692","https://openalex.org/W2911964244","https://openalex.org/W2952370363","https://openalex.org/W3016263887","https://openalex.org/W3087228565","https://openalex.org/W3106822077","https://openalex.org/W3122724846","https://openalex.org/W3123231639","https://openalex.org/W3124946654","https://openalex.org/W3125983399","https://openalex.org/W3126357747","https://openalex.org/W3141714916","https://openalex.org/W3168825659","https://openalex.org/W3204980230","https://openalex.org/W4225139287","https://openalex.org/W4285404671","https://openalex.org/W4327586667","https://openalex.org/W4362465228","https://openalex.org/W4368340961","https://openalex.org/W4385789663","https://openalex.org/W4387004938","https://openalex.org/W4387327959","https://openalex.org/W4387336358","https://openalex.org/W4387492058","https://openalex.org/W4388515789","https://openalex.org/W4391977778","https://openalex.org/W4396677616","https://openalex.org/W4406923810","https://openalex.org/W4407166485","https://openalex.org/W4407592299","https://openalex.org/W4408973509","https://openalex.org/W4412421009","https://openalex.org/W4412907177","https://openalex.org/W7083311231"],"related_works":[],"abstract_inverted_index":{"ABSTRACT":[0],"Review":[1],"helpfulness":[2,33],"prediction":[3],"(RHP)":[4],"is":[5,21],"critical":[6],"for":[7,112,119,210,223],"alleviating":[8],"information":[9,76],"overload":[10],"and":[11,25,41,44,66,69,103,122,128,131,137,176,186,188,197,217,219],"supporting":[12],"reliable":[13],"decision":[14],"making":[15],"on":[16,48,155,229],"e\u2010commerce":[17,161],"platforms,":[18],"yet":[19],"it":[20],"challenged":[22],"by":[23],"unstructured":[24],"multimodal":[26,140,178,208],"review":[27,64,99,101,226],"content":[28],"as":[29,31],"well":[30],"distorted":[32],"signals.":[34],"Prior":[35],"studies":[36,190],"have":[37],"examined":[38],"textual,":[39],"structural,":[40],"reviewer\u2010related":[42],"determinants":[43],"built":[45],"models":[46,98,180],"based":[47],"manually":[49],"engineered":[50],"features":[51,124],"or":[52],"deep":[53,93,173],"learning,":[54],"but":[55],"most":[56],"approaches":[57],"remain":[58],"text\u2010centric,":[59],"make":[60],"limited":[61],"use":[62],"of":[63,159,183,194],"images":[65],"structured":[67,104],"metadata,":[68],"offer":[70],"little":[71],"interpretability":[72],"regarding":[73],"how":[74],"different":[75],"sources":[77],"contribute":[78],"to":[79],"predictions.":[80],"To":[81],"address":[82],"these":[83],"issues,":[84],"we":[85],"propose":[86],"Attentive":[87],"Gated":[88],"Multimodal":[89],"Fusion":[90],"(AGMF),":[91],"a":[92,108,115,138,156],"learning":[94,174],"framework":[95],"that":[96,142,164,212],"jointly":[97],"text,":[100,215],"images,":[102,216],"metadata.":[105],"AGMF":[106,165],"employs":[107],"pre\u2010trained":[109],"language":[110],"model":[111],"textual":[113],"representations,":[114],"convolutional":[116],"neural":[117],"network":[118],"visual":[120],"features,":[121],"metadata":[123,218],"capturing":[125],"reviewer":[126],"characteristics":[127],"behavioural":[129],"signals,":[130],"fuses":[132],"them":[133],"through":[134],"cross\u2010modal":[135],"attention":[136],"gated":[139],"unit":[141],"adaptively":[143],"weights":[144],"each":[145,195],"modality":[146,196],"at":[147],"the":[148,192,198],"instance":[149],"level,":[150],"providing":[151],"modality\u2010level":[152],"interpretability.":[153],"Experiments":[154],"large\u2010scale":[157],"dataset":[158],"Chinese":[160],"reviews":[162],"show":[163],"consistently":[166],"outperforms":[167],"traditional":[168],"machine\u2010learning":[169],"methods,":[170],"strong":[171],"single\u2010modality":[172],"baselines,":[175],"competitive":[177],"fusion":[179,200],"in":[181],"terms":[182],"accuracy,":[184],"F1\u2010score,":[185],"AUC,":[187],"ablation":[189],"confirm":[191],"effectiveness":[193],"proposed":[199],"mechanism.":[201],"Overall,":[202],"this":[203],"study":[204],"contributes":[205],"an":[206],"interpretable":[207],"architecture":[209],"RHP":[211],"effectively":[213],"integrates":[214],"offers":[220],"practical":[221],"guidance":[222],"designing":[224],"intelligent":[225],"filtering":[227],"systems":[228],"online":[230],"platforms.":[231]},"counts_by_year":[],"updated_date":"2026-03-10T14:07:55.174380","created_date":"2026-03-09T00:00:00"}
