{"id":"https://openalex.org/W3032990727","doi":"https://doi.org/10.1145/3372278.3390713","title":"Fake News Detection via Knowledge-driven Multimodal Graph Convolutional Networks","display_name":"Fake News Detection via Knowledge-driven Multimodal Graph Convolutional Networks","publication_year":2020,"publication_date":"2020-06-02","ids":{"openalex":"https://openalex.org/W3032990727","doi":"https://doi.org/10.1145/3372278.3390713","mag":"3032990727"},"language":"en","primary_location":{"id":"doi:10.1145/3372278.3390713","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3372278.3390713","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 International Conference on Multimedia Retrieval","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/A5007267891","display_name":"Youze Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Youze Wang","raw_affiliation_strings":["Hefei University of Technology, HeFei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hefei University of Technology, HeFei, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073601707","display_name":"Shengsheng Qian","orcid":"https://orcid.org/0000-0001-9488-2208"},"institutions":[{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shengsheng Qian","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences &amp; University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences &amp; University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101766936","display_name":"Jun Hu","orcid":"https://orcid.org/0000-0003-1277-6802"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Hu","raw_affiliation_strings":["Hefei University of Technology, HeFei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hefei University of Technology, HeFei, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108683740","display_name":"Quan Fang","orcid":"https://orcid.org/0000-0003-4190-1529"},"institutions":[{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Quan Fang","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences &amp; University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences &amp; University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022636178","display_name":"Changsheng Xu","orcid":"https://orcid.org/0000-0001-8343-9665"},"institutions":[{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changsheng Xu","raw_affiliation_strings":["Hefei University of Technology, Institute of Automation, Chinese Academy of Sciences &amp; University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hefei University of Technology, Institute of Automation, Chinese Academy of Sciences &amp; University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I4210165038","https://openalex.org/I16365422"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5007267891"],"corresponding_institution_ids":["https://openalex.org/I16365422"],"apc_list":null,"apc_paid":null,"fwci":36.3341,"has_fulltext":false,"cited_by_count":175,"citation_normalized_percentile":{"value":0.99697827,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"540","last_page":"547"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11147","display_name":"Misinformation and Its Impacts","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T11147","display_name":"Misinformation and Its Impacts","score":1.0,"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/T10028","display_name":"Topic Modeling","score":0.9878000020980835,"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/T14347","display_name":"Big Data and Digital Economy","score":0.9703999757766724,"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":0.8518730401992798},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5952851176261902},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.5719830393791199},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5614987015724182},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5239548683166504},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.4771687090396881},{"id":"https://openalex.org/keywords/semantic-gap","display_name":"Semantic gap","score":0.4240516424179077},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3845972418785095},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.33443427085876465},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.16020864248275757},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.14432954788208008},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.134256511926651}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8518730401992798},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5952851176261902},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.5719830393791199},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5614987015724182},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5239548683166504},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.4771687090396881},{"id":"https://openalex.org/C86034646","wikidata":"https://www.wikidata.org/wiki/Q474311","display_name":"Semantic gap","level":4,"score":0.4240516424179077},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3845972418785095},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.33443427085876465},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.16020864248275757},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.14432954788208008},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.134256511926651},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3372278.3390713","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3372278.3390713","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1593045043","https://openalex.org/W1975594555","https://openalex.org/W2032897813","https://openalex.org/W2050103272","https://openalex.org/W2084591134","https://openalex.org/W2100341149","https://openalex.org/W2114544510","https://openalex.org/W2138605095","https://openalex.org/W2153579005","https://openalex.org/W2294978630","https://openalex.org/W2737907513","https://openalex.org/W2741930413","https://openalex.org/W2742330194","https://openalex.org/W2766462585","https://openalex.org/W2788667846","https://openalex.org/W2809476703","https://openalex.org/W2896675016","https://openalex.org/W2912305564","https://openalex.org/W2962946486","https://openalex.org/W2963523292","https://openalex.org/W2963653811","https://openalex.org/W2963691861","https://openalex.org/W2963964898","https://openalex.org/W2981972397","https://openalex.org/W2982137384","https://openalex.org/W4285719527","https://openalex.org/W4289673878","https://openalex.org/W6754169603"],"related_works":["https://openalex.org/W2750434199","https://openalex.org/W64303689","https://openalex.org/W2347374138","https://openalex.org/W2129428289","https://openalex.org/W2050635624","https://openalex.org/W2101447046","https://openalex.org/W2091753323","https://openalex.org/W2168037874","https://openalex.org/W2078285696","https://openalex.org/W2135728080"],"abstract_inverted_index":{"Nowadays,":[0],"with":[1],"the":[2,36,45,52,55,65,87,92,96,119,125,164,211,225],"rapid":[3],"development":[4],"of":[5,13,27,44,54,71,84,95,142,166,177,190,214,227],"social":[6],"media,":[7],"there":[8],"is":[9,58],"a":[10,25,59,72,76,109,134,154,204],"great":[11],"deal":[12],"news":[14,22,39,101,139,200],"produced":[15],"every":[16],"day.":[17],"How":[18],"to":[19,74,117,192,197,209],"detect":[20,80],"fake":[21,81,100,138,199],"automatically":[23],"from":[24,51,184],"large":[26],"multimedia":[28],"posts":[29],"has":[30],"become":[31],"very":[32],"important":[33],"for":[34,137,161],"people,":[35],"government":[37],"and":[38,68,79,130],"recommendation":[40],"sites.":[41],"However,":[42],"most":[43],"existing":[46],"approaches":[47],"either":[48],"extract":[49,210],"features":[50,67,70],"text":[53,93,144],"post":[56,73,97],"which":[57,98,156],"single":[60],"modality":[61],"or":[62],"simply":[63],"concatenate":[64],"visual":[66,131,173],"textual":[69,126],"get":[75],"multimodal":[77],"feature":[78],"news.":[82],"Most":[83],"them":[85,152],"ignore":[86],"background":[88],"knowledge":[89,128,183,186],"hidden":[90],"in":[91],"content":[94,145],"facilitates":[99],"detection.":[102,140,201],"To":[103],"address":[104],"these":[105,215],"issues,":[106],"we":[107,150,169],"propose":[108],"novel":[110],"Knowledge-driven":[111],"Multimodal":[112],"Graph":[113],"Convolutional":[114],"Network":[115],"(KMGCN)":[116],"model":[118,158],"semantic":[120,212],"representations":[121],"by":[122],"jointly":[123],"modeling":[124],"information,":[127],"concepts":[129],"information":[132,174,196],"into":[133,153],"unified":[135],"framework":[136],"Instead":[141],"viewing":[143],"as":[146,175,188],"word":[147],"sequences":[148],"normally,":[149],"convert":[151,172],"graph,":[155],"can":[157],"non-consecutive":[159],"phrases":[160],"better":[162],"obtaining":[163],"composition":[165],"semantics.":[167],"Besides,":[168],"not":[170],"only":[171],"nodes":[176,189],"graphs":[178,191],"but":[179],"also":[180],"retrieve":[181],"external":[182],"real-world":[185,222],"graph":[187,206],"provide":[193],"complementary":[194],"semantics":[195],"improve":[198],"We":[202],"utilize":[203],"well-designed":[205],"convolutional":[207],"network":[208],"representation":[213],"graphs.":[216],"Extensive":[217],"experiments":[218],"on":[219],"two":[220],"public":[221],"datasets":[223],"illustrate":[224],"validation":[226],"our":[228],"approach.":[229]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":35},{"year":2024,"cited_by_count":38},{"year":2023,"cited_by_count":50},{"year":2022,"cited_by_count":31},{"year":2021,"cited_by_count":17},{"year":2020,"cited_by_count":1}],"updated_date":"2026-05-02T08:42:23.175194","created_date":"2025-10-10T00:00:00"}
