{"id":"https://openalex.org/W4396735678","doi":"https://doi.org/10.1145/3589334.3645478","title":"Semantic Evolvement Enhanced Graph Autoencoder for Rumor Detection","display_name":"Semantic Evolvement Enhanced Graph Autoencoder for Rumor Detection","publication_year":2024,"publication_date":"2024-05-08","ids":{"openalex":"https://openalex.org/W4396735678","doi":"https://doi.org/10.1145/3589334.3645478"},"language":"en","primary_location":{"id":"doi:10.1145/3589334.3645478","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3589334.3645478","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2024","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/A5050080996","display_name":"Xiang Tao","orcid":"https://orcid.org/0009-0001-5756-8970"},"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":true,"raw_author_name":"Xiang Tao","raw_affiliation_strings":["CRIPAC, MAIS, Institute of Automation, Chinese Academy of Sciences & School of Artificial Intelligence, University of Chinese Academy of Sciences, Haidian, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0001-5756-8970","affiliations":[{"raw_affiliation_string":"CRIPAC, MAIS, Institute of Automation, Chinese Academy of Sciences & School of Artificial Intelligence, University of Chinese Academy of Sciences, Haidian, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089131316","display_name":"Liang Wang","orcid":"https://orcid.org/0000-0002-4714-7582"},"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":"Liang Wang","raw_affiliation_strings":["CRIPAC, MAIS, Institute of Automation, Chinese Academy of Sciences & School of Artificial Intelligence, University of Chinese Academy of Sciences, Haidian, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4714-7582","affiliations":[{"raw_affiliation_string":"CRIPAC, MAIS, Institute of Automation, Chinese Academy of Sciences & School of Artificial Intelligence, University of Chinese Academy of Sciences, Haidian, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100409503","display_name":"Qiang Liu","orcid":"https://orcid.org/0000-0002-9233-3827"},"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":"Qiang Liu","raw_affiliation_strings":["CRIPAC, MAIS, Institute of Automation, Chinese Academy of Sciences & School of Artificial Intelligence, University of Chinese Academy of Sciences, Haidian, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-9233-3827","affiliations":[{"raw_affiliation_string":"CRIPAC, MAIS, Institute of Automation, Chinese Academy of Sciences & School of Artificial Intelligence, University of Chinese Academy of Sciences, Haidian, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047523245","display_name":"Shu Wu","orcid":"https://orcid.org/0000-0003-2164-3577"},"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":"Shu Wu","raw_affiliation_strings":["CRIPAC, MAIS, Institute of Automation, Chinese Academy of Sciences & School of Artificial Intelligence, University of Chinese Academy of Sciences, Haidian, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-2164-3577","affiliations":[{"raw_affiliation_string":"CRIPAC, MAIS, Institute of Automation, Chinese Academy of Sciences & School of Artificial Intelligence, University of Chinese Academy of Sciences, Haidian, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5115602506","display_name":"Liang Wang","orcid":"https://orcid.org/0000-0001-5224-8647"},"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":"Liang Wang","raw_affiliation_strings":["CRIPAC, MAIS, Institute of Automation, Chinese Academy of Sciences & School of Artificial Intelligence, University of Chinese Academy of Sciences, Haidian, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-5224-8647","affiliations":[{"raw_affiliation_string":"CRIPAC, MAIS, Institute of Automation, Chinese Academy of Sciences & School of Artificial Intelligence, University of Chinese Academy of Sciences, Haidian, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5050080996"],"corresponding_institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":6.4466,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.96055676,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"4150","last_page":"4159"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11147","display_name":"Misinformation and Its Impacts","score":0.9997000098228455,"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":0.9997000098228455,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9667999744415283,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9218999743461609,"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/autoencoder","display_name":"Autoencoder","score":0.8543053865432739},{"id":"https://openalex.org/keywords/rumor","display_name":"Rumor","score":0.8391895294189453},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.71640944480896},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5128655433654785},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43604129552841187},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.24888846278190613},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.13660776615142822}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.8543053865432739},{"id":"https://openalex.org/C2780469804","wikidata":"https://www.wikidata.org/wiki/Q878352","display_name":"Rumor","level":2,"score":0.8391895294189453},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.71640944480896},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5128655433654785},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43604129552841187},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.24888846278190613},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.13660776615142822},{"id":"https://openalex.org/C39549134","wikidata":"https://www.wikidata.org/wiki/Q133080","display_name":"Public relations","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3589334.3645478","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3589334.3645478","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2024","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7486045167","display_name":null,"funder_award_id":"62206291, 62372454, 62141608","funder_id":"https://openalex.org/F4320323817","funder_display_name":"Universitas Brawijaya"}],"funders":[{"id":"https://openalex.org/F4320323817","display_name":"Universitas Brawijaya","ror":"https://ror.org/01wk3d929"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W1975594555","https://openalex.org/W2084591134","https://openalex.org/W2577888896","https://openalex.org/W2683299720","https://openalex.org/W2737907513","https://openalex.org/W2741930413","https://openalex.org/W2742144412","https://openalex.org/W2767404761","https://openalex.org/W2798787718","https://openalex.org/W2899457523","https://openalex.org/W2951288507","https://openalex.org/W2983067441","https://openalex.org/W2997128522","https://openalex.org/W3080997787","https://openalex.org/W3095746859","https://openalex.org/W3101707147","https://openalex.org/W3153427360","https://openalex.org/W3154503084","https://openalex.org/W3157089686","https://openalex.org/W3173151551","https://openalex.org/W3192113933","https://openalex.org/W3204453541","https://openalex.org/W3205778609","https://openalex.org/W4205480697","https://openalex.org/W4220885976","https://openalex.org/W4221023051","https://openalex.org/W4221122068","https://openalex.org/W4221148143","https://openalex.org/W4224310546","https://openalex.org/W4224313013","https://openalex.org/W4224313288","https://openalex.org/W4224318954","https://openalex.org/W4284687330","https://openalex.org/W4290876361","https://openalex.org/W4306818238","https://openalex.org/W4312248975","https://openalex.org/W4312584871","https://openalex.org/W4312824836","https://openalex.org/W4327525152","https://openalex.org/W4367046785","https://openalex.org/W4367047181","https://openalex.org/W4379382506","https://openalex.org/W4381244004","https://openalex.org/W4389610092","https://openalex.org/W6600175266","https://openalex.org/W6600567258","https://openalex.org/W6743090812"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2372853429","https://openalex.org/W2793319716","https://openalex.org/W3110636174","https://openalex.org/W4210503589","https://openalex.org/W4389515667","https://openalex.org/W4220775285","https://openalex.org/W2891286602"],"abstract_inverted_index":{"Due":[0],"to":[1,55,155,160,174],"the":[2,28,40,123,149,157,162,177,188,195],"rapid":[3],"spread":[4],"of":[5,31,42,46,95,129,165,190],"rumors":[6,141,166],"on":[7,182],"social":[8],"media,":[9],"rumor":[10,20,65,204],"detection":[11,21,66],"has":[12],"become":[13],"an":[14],"extremely":[15],"important":[16],"challenge.":[17],"Recently,":[18],"numerous":[19],"models":[22],"which":[23,51],"utilize":[24],"textual":[25],"information":[26,45,94,106,118,147],"and":[27,63,102,111,119,132,135,167,202],"propagation":[29,49,120,131],"structure":[30,121],"events":[32,96],"have":[33],"been":[34],"proposed.":[35],"However,":[36],"these":[37],"methods":[38],"overlook":[39],"importance":[41],"semantic":[43,76,92,100,104,116,145],"evolvement":[44,77,93,105,117,146],"event":[47,130],"in":[48,59,86,148,153,198],"process,":[50],"is":[52],"often":[53],"challenging":[54],"be":[56],"truly":[57],"learned":[58],"supervised":[60],"training":[61],"paradigms":[62],"traditional":[64],"methods.":[67],"To":[68],"address":[69],"this":[70,87],"issue,":[71],"we":[72,169],"propose":[73],"a":[74,126,171],"novel":[75],"enhanced":[78],"Graph":[79],"Autoencoder":[80],"for":[81],"Rumor":[82],"Detection":[83],"(GARD)":[84],"model":[85,90,124],"paper.":[88],"The":[89],"learns":[91],"by":[97,143],"capturing":[98,144],"local":[99],"changes":[101],"global":[103],"through":[107],"specific":[108],"graph":[109],"autoencoder":[110],"reconstruction":[112],"strategies.":[113],"By":[114],"combining":[115],"information,":[122],"achieves":[125],"comprehensive":[127],"understanding":[128],"perform":[133],"accurate":[134],"robust":[136],"detection,":[137],"while":[138],"also":[139],"detecting":[140],"earlier":[142],"early":[150,203],"stages.":[151],"Moreover,":[152],"order":[154],"enhance":[156],"model's":[158,178],"ability":[159],"learn":[161],"distinct":[163],"patterns":[164],"non-rumors,":[168],"introduce":[170],"uniformity":[172],"regularizer":[173],"further":[175],"improve":[176],"performance.":[179],"Experimental":[180],"results":[181],"three":[183],"public":[184],"benchmark":[185],"datasets":[186],"confirm":[187],"superiority":[189],"our":[191],"GARD":[192],"method":[193],"over":[194],"state-of-the-art":[196],"approaches":[197],"both":[199],"overall":[200],"performance":[201],"detection.":[205]},"counts_by_year":[{"year":2025,"cited_by_count":6}],"updated_date":"2025-12-26T23:08:49.675405","created_date":"2025-10-10T00:00:00"}