{"id":"https://openalex.org/W4387130536","doi":"https://doi.org/10.1145/3613330.3613340","title":"Unsupervised Cross-Domain Rumor Detection from Multiple Sources Based on RoBERTa and Multi-CNN","display_name":"Unsupervised Cross-Domain Rumor Detection from Multiple Sources Based on RoBERTa and Multi-CNN","publication_year":2023,"publication_date":"2023-07-27","ids":{"openalex":"https://openalex.org/W4387130536","doi":"https://doi.org/10.1145/3613330.3613340"},"language":"en","primary_location":{"id":"doi:10.1145/3613330.3613340","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3613330.3613340","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 7th International Conference on Deep Learning Technologies","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/A5035509689","display_name":"Taozheng Zhang","orcid":"https://orcid.org/0000-0002-4689-3276"},"institutions":[{"id":"https://openalex.org/I75689368","display_name":"Communication University of China","ror":"https://ror.org/04facbs33","country_code":"CN","type":"education","lineage":["https://openalex.org/I75689368"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Taozheng Zhang","raw_affiliation_strings":["School of Information and Communication Engineering, Communication University of China, China"],"raw_orcid":"https://orcid.org/0000-0002-4689-3276","affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Communication University of China, China","institution_ids":["https://openalex.org/I75689368"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5106485378","display_name":"Shuaidong Hu","orcid":"https://orcid.org/0009-0002-5076-3367"},"institutions":[{"id":"https://openalex.org/I75689368","display_name":"Communication University of China","ror":"https://ror.org/04facbs33","country_code":"CN","type":"education","lineage":["https://openalex.org/I75689368"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuaidong Hu","raw_affiliation_strings":["School of Information and Communication Engineering, Communication University of China, China"],"raw_orcid":"https://orcid.org/0009-0002-5076-3367","affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Communication University of China, China","institution_ids":["https://openalex.org/I75689368"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I75689368"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"85","last_page":"90"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11147","display_name":"Misinformation and Its Impacts","score":0.9991000294685364,"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":0.9991000294685364,"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":0.9681000113487244,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9643999934196472,"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/rumor","display_name":"Rumor","score":0.8642697334289551},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8297380208969116},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.7333393692970276},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.6767755746841431},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6342132687568665},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.599611759185791},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.5479367971420288},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5471673011779785},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5143734216690063},{"id":"https://openalex.org/keywords/microblogging","display_name":"Microblogging","score":0.4397856593132019},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.42503926157951355},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.35165128111839294},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35024404525756836}],"concepts":[{"id":"https://openalex.org/C2780469804","wikidata":"https://www.wikidata.org/wiki/Q878352","display_name":"Rumor","level":2,"score":0.8642697334289551},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8297380208969116},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.7333393692970276},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.6767755746841431},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6342132687568665},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.599611759185791},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.5479367971420288},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5471673011779785},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5143734216690063},{"id":"https://openalex.org/C143275388","wikidata":"https://www.wikidata.org/wiki/Q92438","display_name":"Microblogging","level":3,"score":0.4397856593132019},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.42503926157951355},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.35165128111839294},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35024404525756836},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","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},{"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/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3613330.3613340","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3613330.3613340","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 7th International Conference on Deep Learning Technologies","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":14,"referenced_works":["https://openalex.org/W1832693441","https://openalex.org/W1975594555","https://openalex.org/W2742144412","https://openalex.org/W2897757923","https://openalex.org/W2904209271","https://openalex.org/W2974291863","https://openalex.org/W3021632667","https://openalex.org/W3124219615","https://openalex.org/W3142859878","https://openalex.org/W3210022786","https://openalex.org/W4206218388","https://openalex.org/W4297969478","https://openalex.org/W6637618735","https://openalex.org/W6688325169"],"related_works":["https://openalex.org/W2014794499","https://openalex.org/W2353483694","https://openalex.org/W2001642679","https://openalex.org/W2807186976","https://openalex.org/W3183901164","https://openalex.org/W3135818718","https://openalex.org/W4290188444","https://openalex.org/W3176438653","https://openalex.org/W3167935049","https://openalex.org/W3003905048"],"abstract_inverted_index":{"Internet":[0],"rumors":[1,36],"are":[2,18],"prevalent":[3],"and":[4,44,69,78,114,130,141],"harmful":[5],"to":[6,21,90,98,139],"society.":[7],"Hence,":[8],"automatic":[9],"rumor":[10,33,61,169],"detection":[11,62],"is":[12],"essential.":[13],"However,":[14],"supervised":[15],"learning":[16,77,167],"methods":[17,48],"impractical":[19],"due":[20],"the":[22,29,86,92,99,115,123,157,161],"high":[23],"cost":[24],"of":[25,32,125,128],"data":[26],"labeling":[27],"in":[28,133,168],"early":[30],"stage":[31],"propagation.":[34],"Moreover,":[35],"can":[37,108,117],"originate":[38],"from":[39,94],"multiple":[40,70,95,134],"different":[41],"source":[42,96,129],"domains,":[43],"single-source":[45],"domain":[46,80],"adaptation":[47,146],"cannot":[49],"handle":[50],"this":[51,57],"scenario.":[52],"To":[53],"address":[54],"these":[55],"challenges,":[56],"paper":[58],"proposes":[59],"a":[60],"model":[63,68,83,159],"based":[64,164],"on":[65,149,165],"RoBERTa":[66],"pre-training":[67],"convolutional":[71],"neural":[72],"networks":[73],"that":[74,104,156],"combines":[75],"unsupervised":[76],"multi-source":[79],"adaptation.":[81],"The":[82],"only":[84],"uses":[85],"microblog":[87],"text":[88,106],"content":[89],"transfer":[91,166],"knowledge":[93],"domains":[97,132],"target":[100,131],"domain.":[101],"We":[102],"find":[103],"dynamic":[105,144],"representations":[107],"be":[109,118],"effectively":[110],"extracted":[111],"by":[112,121],"RoBERTa,":[113],"discrepancy":[116],"better":[119],"reduced":[120],"aligning":[122],"distributions":[124],"each":[126],"pair":[127],"feature":[135],"spaces.":[136],"Additionally,":[137],"according":[138],"F1":[140],"time":[142],"cost,":[143],"distribution":[145],"performs":[147],"best":[148],"quantitative":[150],"evaluation.":[151],"Finally,":[152],"extensive":[153],"experiments":[154],"demonstrate":[155],"proposed":[158],"outperforms":[160],"baseline":[162],"models":[163],"detection.":[170]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}