{"id":"https://openalex.org/W4312825041","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892819","title":"Rumor Detection with Adversarial Training and Supervised Contrastive Learning","display_name":"Rumor Detection with Adversarial Training and Supervised Contrastive Learning","publication_year":2022,"publication_date":"2022-07-18","ids":{"openalex":"https://openalex.org/W4312825041","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892819"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn55064.2022.9892819","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892819","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","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 International Joint Conference on Neural Networks (IJCNN)","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/A5043166902","display_name":"Sunjun Dong","orcid":null},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Sunjun Dong","raw_affiliation_strings":["School of Computer Science and Technology, Soochow University,Suzhou,China","School of Computer Science and Technology, Soochow University, Suzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Soochow University,Suzhou,China","institution_ids":["https://openalex.org/I3923682"]},{"raw_affiliation_string":"School of Computer Science and Technology, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042912655","display_name":"Qian Zhong","orcid":"https://orcid.org/0000-0001-7651-7872"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhong Qian","raw_affiliation_strings":["School of Computer Science and Technology, Soochow University,Suzhou,China","School of Computer Science and Technology, Soochow University, Suzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Soochow University,Suzhou,China","institution_ids":["https://openalex.org/I3923682"]},{"raw_affiliation_string":"School of Computer Science and Technology, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100695549","display_name":"Peifeng Li","orcid":"https://orcid.org/0000-0003-4850-3128"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peifeng Li","raw_affiliation_strings":["School of Computer Science and Technology, Soochow University,Suzhou,China","School of Computer Science and Technology, Soochow University, Suzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Soochow University,Suzhou,China","institution_ids":["https://openalex.org/I3923682"]},{"raw_affiliation_string":"School of Computer Science and Technology, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5043166902"],"corresponding_institution_ids":["https://openalex.org/I3923682"],"apc_list":null,"apc_paid":null,"fwci":0.2907,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.62925926,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"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/T10028","display_name":"Topic Modeling","score":0.9545000195503235,"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/T13718","display_name":"Media Influence and Politics","score":0.949400007724762,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/rumor","display_name":"Rumor","score":0.8437937498092651},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8054854869842529},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7889657616615295},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.728488028049469},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6030845046043396},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5546938180923462},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.4523986577987671},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.42142254114151},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.35255980491638184},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.19063851237297058},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.08850392699241638}],"concepts":[{"id":"https://openalex.org/C2780469804","wikidata":"https://www.wikidata.org/wiki/Q878352","display_name":"Rumor","level":2,"score":0.8437937498092651},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8054854869842529},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7889657616615295},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.728488028049469},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6030845046043396},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5546938180923462},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.4523986577987671},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.42142254114151},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.35255980491638184},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.19063851237297058},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.08850392699241638},{"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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn55064.2022.9892819","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892819","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","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 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4099999964237213,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G506606176","display_name":null,"funder_award_id":"61836007,62006167","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/F4320327518","display_name":"Priority Academic Program Development of Jiangsu Higher Education Institutions","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1638051351","https://openalex.org/W1945616565","https://openalex.org/W1975594555","https://openalex.org/W2032897813","https://openalex.org/W2084591134","https://openalex.org/W2142869398","https://openalex.org/W2577888896","https://openalex.org/W2609512471","https://openalex.org/W2741930413","https://openalex.org/W2742144412","https://openalex.org/W2788235048","https://openalex.org/W2798787718","https://openalex.org/W2897757923","https://openalex.org/W2911715381","https://openalex.org/W2912078280","https://openalex.org/W2964015378","https://openalex.org/W2976922468","https://openalex.org/W2997128522","https://openalex.org/W2997976265","https://openalex.org/W3017402509","https://openalex.org/W3034524234","https://openalex.org/W3034531060","https://openalex.org/W3091887019","https://openalex.org/W3109142382","https://openalex.org/W3202954464","https://openalex.org/W4287614078","https://openalex.org/W4297733535","https://openalex.org/W6640425456","https://openalex.org/W6726873649","https://openalex.org/W6732431570","https://openalex.org/W6736903189","https://openalex.org/W6745537798","https://openalex.org/W6784874100","https://openalex.org/W6801961247"],"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":{"The":[0,124],"proliferation":[1],"of":[2,37,42,51,122],"rumors":[3,27],"on":[4,28,127],"social":[5,14,29],"media":[6],"has":[7],"seriously":[8],"affected":[9],"personal":[10],"life,":[11],"even":[12],"threatened":[13],"security":[15],"and":[16,40,46,70,117,132],"stability.":[17],"Therefore,":[18],"there":[19],"is":[20],"an":[21],"urgent":[22],"need":[23],"to":[24,56,84],"automatically":[25],"detect":[26],"media.":[30],"However,":[31],"existing":[32],"methods":[33],"lack":[34],"robustness":[35,121],"because":[36],"high":[38],"dimension":[39],"sparsity":[41],"natural":[43],"language":[44],"texts":[45],"one":[47],"hundreds":[48],"description":[49],"ways":[50],"same":[52,92],"events.":[53],"In":[54],"order":[55],"solve":[57],"this":[58],"issue,":[59],"we":[60,94],"propose":[61],"a":[62,86,97],"novel":[63],"model":[64],"ATSCL,":[65],"which":[66,102],"integrates":[67],"adversarial":[68,79],"training":[69],"supervised":[71,98],"contrastive":[72,99],"learning.":[73],"We":[74],"enhance":[75,119],"ATSCL":[76],"by":[77],"adding":[78],"perturbations":[80],"in":[81],"embedding":[82],"layer":[83],"obtain":[85],"more":[87],"robust":[88],"model.":[89],"At":[90],"the":[91,105,112,120],"time,":[93],"also":[95],"utilize":[96],"learning":[100],"objective":[101],"can":[103],"shorten":[104],"distance":[106,113],"between":[107,114],"rumor":[108],"samples,":[109,116],"push":[110],"away":[111],"non-rumor":[115],"further":[118],"ATSCL.":[123],"experimental":[125],"results":[126],"two":[128],"real-word":[129],"datasets":[130],"Twitter15":[131],"Twitter16":[133],"demonstrate":[134],"that":[135],"our":[136],"method":[137],"outperforms":[138],"several":[139],"state-of-the-art":[140],"methods.":[141]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}