{"id":"https://openalex.org/W4408354163","doi":"https://doi.org/10.1109/icassp49660.2025.10887787","title":"Simple Adaptive Spectrum Graph Filters for Rumor Detection","display_name":"Simple Adaptive Spectrum Graph Filters for Rumor Detection","publication_year":2025,"publication_date":"2025-03-12","ids":{"openalex":"https://openalex.org/W4408354163","doi":"https://doi.org/10.1109/icassp49660.2025.10887787"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49660.2025.10887787","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10887787","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5107831201","display_name":"Nan Yu","orcid":"https://orcid.org/0009-0009-9940-8906"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nanjun Yu","raw_affiliation_strings":["East China Normal University,Shanghai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"East China Normal University,Shanghai,China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101849003","display_name":"Qiang Cao","orcid":"https://orcid.org/0000-0001-8160-8883"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiang Cao","raw_affiliation_strings":["East China Normal University,Shanghai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"East China Normal University,Shanghai,China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"last","author":{"id":null,"display_name":"Zheng Dong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng Dong","raw_affiliation_strings":["ByteDance,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ByteDance,Beijing,China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.980400025844574,"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"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.980400025844574,"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/T11147","display_name":"Misinformation and Its Impacts","score":0.9653000235557556,"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/T12592","display_name":"Opinion Dynamics and Social Influence","score":0.9441999793052673,"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":0.6852340698242188},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6598933339118958},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.64190673828125},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4411773085594177},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3800133764743805},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.27785611152648926}],"concepts":[{"id":"https://openalex.org/C2780469804","wikidata":"https://www.wikidata.org/wiki/Q878352","display_name":"Rumor","level":2,"score":0.6852340698242188},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6598933339118958},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.64190673828125},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4411773085594177},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3800133764743805},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.27785611152648926},{"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},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49660.2025.10887787","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10887787","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W2039298587","https://openalex.org/W2101491865","https://openalex.org/W2158787690","https://openalex.org/W2598170113","https://openalex.org/W2737907513","https://openalex.org/W2741930413","https://openalex.org/W2763572884","https://openalex.org/W2788235048","https://openalex.org/W2798787718","https://openalex.org/W2912636151","https://openalex.org/W2997128522","https://openalex.org/W3028193185","https://openalex.org/W3095521706","https://openalex.org/W3198329374","https://openalex.org/W4205138969","https://openalex.org/W4213144639","https://openalex.org/W4224318954","https://openalex.org/W4312248975","https://openalex.org/W4385658818","https://openalex.org/W4388451055","https://openalex.org/W4393156111","https://openalex.org/W4401480687","https://openalex.org/W6631190155","https://openalex.org/W6720006811","https://openalex.org/W6726873649","https://openalex.org/W6755207826","https://openalex.org/W6767998753","https://openalex.org/W6779733120","https://openalex.org/W6796801894","https://openalex.org/W6797464607","https://openalex.org/W6803519869","https://openalex.org/W6850925396"],"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/W2908713064","https://openalex.org/W2810386322","https://openalex.org/W2801267666"],"abstract_inverted_index":{"Rumor":[0],"detection":[1,56],"has":[2],"become":[3],"an":[4,107],"important":[5],"problem":[6],"on":[7,130,136],"social":[8],"networks.":[9],"Previous":[10],"methods":[11,33],"mostly":[12],"employ":[13],"deep":[14],"learning":[15],"approaches":[16],"to":[17,26,43,120],"extract":[18],"rumor":[19,28],"features":[20],"and":[21,41,91],"apply":[22],"spatial":[23,39],"graph":[24,70,89,117,132],"convolutions":[25],"process":[27],"propagation":[29],"trees.":[30],"However,":[31],"these":[32,50],"face":[34],"inherent":[35],"issues":[36],"in":[37],"the":[38,67,79,87,104,112,116,131],"domain":[40],"struggle":[42],"handle":[44],"global":[45],"structures":[46],"effectively.":[47],"To":[48],"address":[49],"problems,":[51],"we":[52,65,85,126],"propose":[53],"a":[54,74],"new":[55],"model,":[57],"Simple":[58],"Adaptive":[59],"Spectrum":[60],"Graph":[61],"Filters":[62],"(SASGF).":[63],"Specifically,":[64],"obtain":[66,121],"original":[68],"parameterized":[69],"filter":[71,92,123],"bank":[72],"through":[73],"truncated":[75],"polynomial,":[76],"which":[77],"reduces":[78],"scale":[80],"of":[81,115],"model":[82],"parameters.":[83],"Next,":[84],"transform":[86],"scalar":[88],"frequencies":[90],"sequences":[93],"into":[94],"rich":[95],"vector":[96],"representations":[97],"via":[98],"representation":[99],"encoding.":[100],"We":[101],"then":[102],"redefine":[103],"filters":[105],"with":[106],"attention":[108],"mechanism":[109],"that":[110,141],"leverages":[111],"positional":[113],"information":[114],"frequency":[118],"sequence":[119],"adaptive":[122],"responses.":[124],"Finally,":[125],"perform":[127],"channel-oriented":[128],"filtering":[129],"signal":[133],"spectrum.":[134],"Experiments":[135],"two":[137],"real-world":[138],"datasets":[139],"show":[140],"our":[142],"method":[143],"outperforms":[144],"existing":[145],"baselines.":[146]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}