{"id":"https://openalex.org/W4412888649","doi":"https://doi.org/10.18653/v1/2025.findings-acl.296","title":"FGDGNN: Fine-Grained Dynamic Graph Neural Network for Rumor Detection on Social Media","display_name":"FGDGNN: Fine-Grained Dynamic Graph Neural Network for Rumor Detection on Social Media","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412888649","doi":"https://doi.org/10.18653/v1/2025.findings-acl.296"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2025.findings-acl.296","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.296","pdf_url":"https://aclanthology.org/2025.findings-acl.296.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: ACL 2025","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2025.findings-acl.296.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101666055","display_name":"Mei Guo","orcid":"https://orcid.org/0000-0002-3899-0885"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mei Guo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100418485","display_name":"Chen Chen","orcid":"https://orcid.org/0000-0002-7099-7905"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen Chen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101032887","display_name":"Chunyan Hou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chunyan Hou","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075742545","display_name":"Yike Wu","orcid":"https://orcid.org/0000-0001-7384-8836"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yike Wu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5062064974","display_name":"Xiaojie Yuan","orcid":"https://orcid.org/0000-0002-5876-6856"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaojie Yuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":15.3228,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.98770608,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"5676","last_page":"5687"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11147","display_name":"Misinformation and Its Impacts","score":0.9994999766349792,"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":0.9994999766349792,"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/T11644","display_name":"Spam and Phishing Detection","score":0.9715999960899353,"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/T12592","display_name":"Opinion Dynamics and Social Influence","score":0.9659000039100647,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/rumor","display_name":"Rumor","score":0.8868752717971802},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7099425792694092},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.5053649544715881},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4602031409740448},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44757017493247986},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.327239453792572},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.21751099824905396},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.16916689276695251}],"concepts":[{"id":"https://openalex.org/C2780469804","wikidata":"https://www.wikidata.org/wiki/Q878352","display_name":"Rumor","level":2,"score":0.8868752717971802},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7099425792694092},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.5053649544715881},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4602031409740448},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44757017493247986},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.327239453792572},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.21751099824905396},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.16916689276695251},{"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:10.18653/v1/2025.findings-acl.296","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.296","pdf_url":"https://aclanthology.org/2025.findings-acl.296.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: ACL 2025","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2025.findings-acl.296","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.296","pdf_url":"https://aclanthology.org/2025.findings-acl.296.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: ACL 2025","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.4399999976158142,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G1776413336","display_name":null,"funder_award_id":"62172237","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4034941058","display_name":null,"funder_award_id":"62077031","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4667360632","display_name":null,"funder_award_id":"62372252","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4787383871","display_name":null,"funder_award_id":"62176028","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5811738602","display_name":null,"funder_award_id":"U1936206","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7560528120","display_name":null,"funder_award_id":"U1936105","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"},{"id":"https://openalex.org/F4320321106","display_name":"Ministry of Education of the People's Republic of China","ror":"https://ror.org/01mv9t934"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412888649.pdf","grobid_xml":"https://content.openalex.org/works/W4412888649.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2372853429","https://openalex.org/W2793319716","https://openalex.org/W3110636174","https://openalex.org/W4210503589","https://openalex.org/W2908713064","https://openalex.org/W2810386322","https://openalex.org/W2801267666","https://openalex.org/W2188429085","https://openalex.org/W2886888575"],"abstract_inverted_index":{"Detecting":[0],"rumors":[1],"on":[2,40,151],"social":[3],"media":[4],"has":[5],"become":[6],"a":[7,60,92],"crucial":[8],"issue.Propagation":[9],"structure-based":[10],"methods":[11],"have":[12],"recently":[13],"attracted":[14],"increasing":[15],"attention.When":[16],"the":[17,23,46,72,81,89,101,106,131,135,138,143,146,166],"propagation":[18,78,103],"structure":[19],"is":[20,28,111],"represented":[21],"by":[22],"dynamic":[24,35,77,84],"graph,":[25],"temporal":[26,42,48,74,115,132],"information":[27,43,75,133],"considered.However,":[29],"existing":[30],"rumor":[31,96],"detection":[32],"models":[33],"using":[34],"graph":[36,79,104,108,139],"typically":[37],"focus":[38],"only":[39],"coarse-grained":[41],"and":[44,53,83,105],"ignore":[45],"fine-grained":[47,73],"dynamics":[49],"within":[50],"individual":[51],"snapshots":[52],"across":[54,117],"snapshots.In":[55],"this":[56],"paper,":[57],"we":[58,98,119,129],"propose":[59,120],"novel":[61],"Fine-Grained":[62],"Dynamic":[63],"Graph":[64],"Neural":[65],"Network":[66],"(FGDGNN)":[67],"model,":[68],"which":[69],"can":[70],"incorporate":[71],"of":[76,145],"in":[80,88,134],"intra-snapshot":[82],"embedding":[85,122],"update":[86,126],"mechanism":[87],"inter-snapshots":[90,136],"into":[91],"unified":[93],"framework":[94],"for":[95],"detection.Specifically,":[97],"first":[99],"construct":[100],"edge-weighted":[102],"edge-aware":[107],"isomorphism":[109],"network":[110],"proposed.To":[112],"obtain":[113],"finegrained":[114],"representations":[116],"snapshots,":[118],"an":[121],"transformation":[123],"layer":[124],"to":[125,141],"node":[127],"embeddings.Finally,":[128],"integrate":[130],"at":[137],"level":[140],"enhance":[142],"effectiveness":[144],"proposed":[147],"model.Extensive":[148],"experiments":[149],"conducted":[150],"three":[152],"public":[153],"realworld":[154],"datasets":[155],"demonstrate":[156],"that":[157],"our":[158],"FGDGNN":[159],"model":[160],"achieves":[161],"significant":[162],"improvements":[163],"compared":[164],"with":[165],"state-of-the-art":[167],"baselines.":[168]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
