{"id":"https://openalex.org/W4320024039","doi":"https://doi.org/10.1109/bigdata55660.2022.10020234","title":"Nothing Stands Alone: Relational Fake News Detection with Hypergraph Neural Networks","display_name":"Nothing Stands Alone: Relational Fake News Detection with Hypergraph Neural Networks","publication_year":2022,"publication_date":"2022-12-17","ids":{"openalex":"https://openalex.org/W4320024039","doi":"https://doi.org/10.1109/bigdata55660.2022.10020234"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata55660.2022.10020234","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata55660.2022.10020234","pdf_url":null,"source":{"id":"https://openalex.org/S4363607709","display_name":"2022 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Big Data (Big Data)","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/A5001637779","display_name":"Ujun Jeong","orcid":"https://orcid.org/0000-0001-5467-0374"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ujun Jeong","raw_affiliation_strings":["Arizona State University,School of Computing and Augmented Intelligence","School of Computing and Augmented Intelligence, Arizona State University"],"affiliations":[{"raw_affiliation_string":"Arizona State University,School of Computing and Augmented Intelligence","institution_ids":["https://openalex.org/I55732556"]},{"raw_affiliation_string":"School of Computing and Augmented Intelligence, Arizona State University","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044455276","display_name":"Kaize Ding","orcid":"https://orcid.org/0000-0001-6684-6752"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kaize Ding","raw_affiliation_strings":["Arizona State University,School of Computing and Augmented Intelligence","School of Computing and Augmented Intelligence, Arizona State University"],"affiliations":[{"raw_affiliation_string":"Arizona State University,School of Computing and Augmented Intelligence","institution_ids":["https://openalex.org/I55732556"]},{"raw_affiliation_string":"School of Computing and Augmented Intelligence, Arizona State University","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040552536","display_name":"Lu Cheng","orcid":"https://orcid.org/0000-0002-2503-2522"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lu Cheng","raw_affiliation_strings":["University of Illinois Chicago,Department of Computer Science","Department of Computer Science, University of Illinois Chicago"],"affiliations":[{"raw_affiliation_string":"University of Illinois Chicago,Department of Computer Science","institution_ids":["https://openalex.org/I39422238"]},{"raw_affiliation_string":"Department of Computer Science, University of Illinois Chicago","institution_ids":["https://openalex.org/I39422238"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054719216","display_name":"Ruocheng Guo","orcid":"https://orcid.org/0000-0002-8522-6142"},"institutions":[{"id":"https://openalex.org/I154935518","display_name":"Royal College of Emergency Medicine","ror":"https://ror.org/04zkbxs23","country_code":"GB","type":"education","lineage":["https://openalex.org/I154935518"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Ruocheng Guo","raw_affiliation_strings":["Bytedance AI Lab,London","Bytedance AI Lab, London"],"affiliations":[{"raw_affiliation_string":"Bytedance AI Lab,London","institution_ids":["https://openalex.org/I154935518"]},{"raw_affiliation_string":"Bytedance AI Lab, London","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058670321","display_name":"Kai Shu","orcid":"https://orcid.org/0000-0002-6043-1764"},"institutions":[{"id":"https://openalex.org/I180949307","display_name":"Illinois Institute of Technology","ror":"https://ror.org/037t3ry66","country_code":"US","type":"education","lineage":["https://openalex.org/I180949307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kai Shu","raw_affiliation_strings":["Illinois Institute of Technology,Department of Computer Science","Department of Computer Science, Illinois Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Illinois Institute of Technology,Department of Computer Science","institution_ids":["https://openalex.org/I180949307"]},{"raw_affiliation_string":"Department of Computer Science, Illinois Institute of Technology","institution_ids":["https://openalex.org/I180949307"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100338946","display_name":"Huan Liu","orcid":"https://orcid.org/0000-0002-3264-7904"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Huan Liu","raw_affiliation_strings":["Arizona State University,School of Computing and Augmented Intelligence","School of Computing and Augmented Intelligence, Arizona State University"],"affiliations":[{"raw_affiliation_string":"Arizona State University,School of Computing and Augmented Intelligence","institution_ids":["https://openalex.org/I55732556"]},{"raw_affiliation_string":"School of Computing and Augmented Intelligence, Arizona State University","institution_ids":["https://openalex.org/I55732556"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5001637779"],"corresponding_institution_ids":["https://openalex.org/I55732556"],"apc_list":null,"apc_paid":null,"fwci":6.1514,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.96495071,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"596","last_page":"605"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11147","display_name":"Misinformation and Its Impacts","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9914000034332275,"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/T11644","display_name":"Spam and Phishing Detection","score":0.9898999929428101,"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":0.7492164373397827},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7310934066772461},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.6283993721008301},{"id":"https://openalex.org/keywords/fake-news","display_name":"Fake news","score":0.499908447265625},{"id":"https://openalex.org/keywords/nothing","display_name":"Nothing","score":0.49726584553718567},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.47604966163635254},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.47294020652770996},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.47284892201423645},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3857696056365967},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35873162746429443},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35704654455184937},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.35426509380340576},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3478877544403076},{"id":"https://openalex.org/keywords/internet-privacy","display_name":"Internet privacy","score":0.23051488399505615},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.2124486267566681}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7492164373397827},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7310934066772461},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.6283993721008301},{"id":"https://openalex.org/C2779756789","wikidata":"https://www.wikidata.org/wiki/Q28549308","display_name":"Fake news","level":2,"score":0.499908447265625},{"id":"https://openalex.org/C136815107","wikidata":"https://www.wikidata.org/wiki/Q154242","display_name":"Nothing","level":2,"score":0.49726584553718567},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.47604966163635254},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.47294020652770996},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.47284892201423645},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3857696056365967},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35873162746429443},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35704654455184937},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.35426509380340576},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3478877544403076},{"id":"https://openalex.org/C108827166","wikidata":"https://www.wikidata.org/wiki/Q175975","display_name":"Internet privacy","level":1,"score":0.23051488399505615},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.2124486267566681},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata55660.2022.10020234","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata55660.2022.10020234","pdf_url":null,"source":{"id":"https://openalex.org/S4363607709","display_name":"2022 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":61,"referenced_works":["https://openalex.org/W569478347","https://openalex.org/W2075585362","https://openalex.org/W2101234009","https://openalex.org/W2102306708","https://openalex.org/W2154455818","https://openalex.org/W2170057991","https://openalex.org/W2470673105","https://openalex.org/W2626914210","https://openalex.org/W2735017898","https://openalex.org/W2742144412","https://openalex.org/W2763572884","https://openalex.org/W2790166049","https://openalex.org/W2892880750","https://openalex.org/W2906971970","https://openalex.org/W2911286998","https://openalex.org/W2951307134","https://openalex.org/W2963277000","https://openalex.org/W2963961878","https://openalex.org/W2997128522","https://openalex.org/W3031781733","https://openalex.org/W3035666843","https://openalex.org/W3038570070","https://openalex.org/W3070920170","https://openalex.org/W3085990079","https://openalex.org/W3094624443","https://openalex.org/W3098829544","https://openalex.org/W3106229813","https://openalex.org/W3119467012","https://openalex.org/W3132450769","https://openalex.org/W3133423348","https://openalex.org/W3153567752","https://openalex.org/W3163083951","https://openalex.org/W3171044370","https://openalex.org/W3187966659","https://openalex.org/W3194651497","https://openalex.org/W3198457408","https://openalex.org/W3202630045","https://openalex.org/W3202656708","https://openalex.org/W4200425753","https://openalex.org/W4214873201","https://openalex.org/W4224313013","https://openalex.org/W4288419263","https://openalex.org/W4294558607","https://openalex.org/W4295312788","https://openalex.org/W4296139502","https://openalex.org/W4297733535","https://openalex.org/W4297782361","https://openalex.org/W4311079930","https://openalex.org/W6675398290","https://openalex.org/W6682494755","https://openalex.org/W6726873649","https://openalex.org/W6732431570","https://openalex.org/W6738964360","https://openalex.org/W6741252931","https://openalex.org/W6753014201","https://openalex.org/W6755207826","https://openalex.org/W6758183469","https://openalex.org/W6760045743","https://openalex.org/W6766978945","https://openalex.org/W6771247989","https://openalex.org/W6779808689"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W4297676672","https://openalex.org/W3009056573","https://openalex.org/W2216420239","https://openalex.org/W2922073769","https://openalex.org/W3011492772","https://openalex.org/W4281702477","https://openalex.org/W2800570524","https://openalex.org/W2499122376"],"abstract_inverted_index":{"Nowadays,":[0],"fake":[1,39,49,101,111],"news":[2,22,40,50,102,112,123,149,181],"easily":[3],"propagates":[4],"through":[5],"online":[6],"social":[7],"networks":[8,63],"and":[9,16,54,77,169],"becomes":[10],"a":[11,106,137,176],"grand":[12],"threat":[13],"to":[14,26,34,43,52,68,135,139],"individuals":[15],"society.":[17],"Assessing":[18],"the":[19,57,70,96,171],"authenticity":[20],"of":[21,179],"is":[23],"challenging":[24],"due":[25],"its":[27,152],"elaborately":[28],"fabricated":[29],"contents,":[30],"making":[31],"it":[32],"difficult":[33],"obtain":[35],"large-scale":[36],"annotations":[37],"for":[38,99],"data.":[41,182],"Due":[42],"such":[44],"data":[45],"scarcity":[46],"issues,":[47,132],"detecting":[48,110],"tends":[51],"fail":[53],"overfit":[55],"in":[56,105],"supervised":[58],"setting.":[59],"Recently,":[60],"graph":[61],"neural":[62],"(GNNs)":[64],"have":[65],"been":[66],"adopted":[67],"leverage":[69,136],"richer":[71],"relational":[72],"information":[73],"among":[74,126,143],"both":[75],"labeled":[76,180],"unlabeled":[78],"instances.":[79],"Despite":[80],"their":[81],"promising":[82],"results,":[83],"they":[84],"are":[85],"inherently":[86],"focused":[87],"on":[88,147,158],"pairwise":[89],"relations":[90,121,150],"between":[91,122],"news,":[92,144],"which":[93],"can":[94,113],"limit":[95],"expressive":[97],"power":[98],"capturing":[100],"that":[103,163],"spreads":[104],"group-level.":[107],"For":[108],"example,":[109],"be":[114],"more":[115],"effective":[116],"when":[117],"we":[118,133],"better":[119],"understand":[120],"pieces":[124],"shared":[125],"susceptible":[127],"users.":[128],"To":[129],"address":[130],"those":[131],"propose":[134],"hypergraph":[138],"represent":[140],"group-wise":[141],"interaction":[142],"while":[145],"focusing":[146],"important":[148],"with":[151,175],"dual-level":[153],"attention":[154],"mechanism.":[155],"Experiments":[156],"based":[157],"two":[159],"benchmark":[160],"datasets":[161],"show":[162],"our":[164],"approach":[165],"yields":[166],"remarkable":[167],"performance":[168,173],"maintains":[170],"high":[172],"even":[174],"small":[177],"subset":[178]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":5}],"updated_date":"2026-03-31T07:56:22.981413","created_date":"2025-10-10T00:00:00"}