{"id":"https://openalex.org/W4391113941","doi":"https://doi.org/10.1109/bigdata59044.2023.10386920","title":"Multimodal One-class Learning for Malicious Online Content Detection","display_name":"Multimodal One-class Learning for Malicious Online Content Detection","publication_year":2023,"publication_date":"2023-12-15","ids":{"openalex":"https://openalex.org/W4391113941","doi":"https://doi.org/10.1109/bigdata59044.2023.10386920"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata59044.2023.10386920","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata59044.2023.10386920","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Big Data (BigData)","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/A5010914442","display_name":"Roberto Corizzo","orcid":"https://orcid.org/0000-0001-8366-6059"},"institutions":[{"id":"https://openalex.org/I181401687","display_name":"American University","ror":"https://ror.org/052w4zt36","country_code":"US","type":"education","lineage":["https://openalex.org/I181401687"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Roberto Corizzo","raw_affiliation_strings":["American University,Department of Computer Science,Washington, DC,USA","Department of Computer Science, American University, Washington, DC, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"American University,Department of Computer Science,Washington, DC,USA","institution_ids":["https://openalex.org/I181401687"]},{"raw_affiliation_string":"Department of Computer Science, American University, Washington, DC, USA","institution_ids":["https://openalex.org/I181401687"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110915759","display_name":"Nora Lewis","orcid":null},"institutions":[{"id":"https://openalex.org/I181401687","display_name":"American University","ror":"https://ror.org/052w4zt36","country_code":"US","type":"education","lineage":["https://openalex.org/I181401687"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nora Lewis","raw_affiliation_strings":["American University,Department of Computer Science,Washington, DC,USA","Department of Computer Science, American University, Washington, DC, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"American University,Department of Computer Science,Washington, DC,USA","institution_ids":["https://openalex.org/I181401687"]},{"raw_affiliation_string":"Department of Computer Science, American University, Washington, DC, USA","institution_ids":["https://openalex.org/I181401687"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066926841","display_name":"Lucas P. Damasceno","orcid":"https://orcid.org/0009-0007-2185-2295"},"institutions":[{"id":"https://openalex.org/I243754102","display_name":"Universidade Federal do Cear\u00e1","ror":"https://ror.org/03srtnf24","country_code":"BR","type":"education","lineage":["https://openalex.org/I243754102"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Lucas P. Damasceno","raw_affiliation_strings":["Federal University of Cear&#x00E1;,Department of Teleinformatics Engineering,Fortaleza,Cear\u00e1,Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Federal University of Cear&#x00E1;,Department of Teleinformatics Engineering,Fortaleza,Cear\u00e1,Brazil","institution_ids":["https://openalex.org/I243754102"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000243854","display_name":"Allison Shafer","orcid":null},"institutions":[{"id":"https://openalex.org/I181401687","display_name":"American University","ror":"https://ror.org/052w4zt36","country_code":"US","type":"education","lineage":["https://openalex.org/I181401687"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Allison Shafer","raw_affiliation_strings":["American University,Department of Computer Science,Washington, DC,USA","Department of Computer Science, American University, Washington, DC, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"American University,Department of Computer Science,Washington, DC,USA","institution_ids":["https://openalex.org/I181401687"]},{"raw_affiliation_string":"Department of Computer Science, American University, Washington, DC, USA","institution_ids":["https://openalex.org/I181401687"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061118449","display_name":"Charles C. Cavalcante","orcid":"https://orcid.org/0000-0002-4198-4064"},"institutions":[{"id":"https://openalex.org/I243754102","display_name":"Universidade Federal do Cear\u00e1","ror":"https://ror.org/03srtnf24","country_code":"BR","type":"education","lineage":["https://openalex.org/I243754102"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Charles C. Cavalcante","raw_affiliation_strings":["Federal University of Cear&#x00E1;,Department of Teleinformatics Engineering,Fortaleza,Cear\u00e1,Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Federal University of Cear&#x00E1;,Department of Teleinformatics Engineering,Fortaleza,Cear\u00e1,Brazil","institution_ids":["https://openalex.org/I243754102"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006915006","display_name":"Zois Boukouvalas","orcid":"https://orcid.org/0000-0002-5131-1891"},"institutions":[{"id":"https://openalex.org/I181401687","display_name":"American University","ror":"https://ror.org/052w4zt36","country_code":"US","type":"education","lineage":["https://openalex.org/I181401687"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zois Boukouvalas","raw_affiliation_strings":["American University,Department of Mathematics and Statistics,Washington, DC,USA","Department of Mathematics and Statistics, American University, Washington, DC, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"American University,Department of Mathematics and Statistics,Washington, DC,USA","institution_ids":["https://openalex.org/I181401687"]},{"raw_affiliation_string":"Department of Mathematics and Statistics, American University, Washington, DC, USA","institution_ids":["https://openalex.org/I181401687"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.1046,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.90333482,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2146","last_page":"2151"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11147","display_name":"Misinformation and Its Impacts","score":0.9937999844551086,"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":0.9937999844551086,"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/T11581","display_name":"Viral Infections and Outbreaks Research","score":0.9907000064849854,"subfield":{"id":"https://openalex.org/subfields/2725","display_name":"Infectious Diseases"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9905999898910522,"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/computer-science","display_name":"Computer science","score":0.7990026473999023},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6101073026657104},{"id":"https://openalex.org/keywords/misinformation","display_name":"Misinformation","score":0.5967540144920349},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5811029672622681},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5469740033149719},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.5351831316947937},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4952954351902008},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.49127525091171265},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.4791388213634491},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.09663182497024536}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7990026473999023},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6101073026657104},{"id":"https://openalex.org/C2776990098","wikidata":"https://www.wikidata.org/wiki/Q13579947","display_name":"Misinformation","level":2,"score":0.5967540144920349},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5811029672622681},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5469740033149719},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.5351831316947937},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4952954351902008},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.49127525091171265},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.4791388213634491},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.09663182497024536},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata59044.2023.10386920","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata59044.2023.10386920","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6700000166893005}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1614298861","https://openalex.org/W1686810756","https://openalex.org/W1970088388","https://openalex.org/W2131498344","https://openalex.org/W2296719434","https://openalex.org/W2338318698","https://openalex.org/W2585508806","https://openalex.org/W3136945483","https://openalex.org/W3138640812","https://openalex.org/W3200466594","https://openalex.org/W3203964276","https://openalex.org/W4205548297","https://openalex.org/W4223512430","https://openalex.org/W4254182148","https://openalex.org/W4294646788","https://openalex.org/W4300964748","https://openalex.org/W4312845117","https://openalex.org/W4313421210","https://openalex.org/W4327955601","https://openalex.org/W4385333457","https://openalex.org/W4385488586","https://openalex.org/W4387871205","https://openalex.org/W6636510571","https://openalex.org/W6637373629"],"related_works":["https://openalex.org/W3197131596","https://openalex.org/W4390616380","https://openalex.org/W4388666321","https://openalex.org/W4205914924","https://openalex.org/W4225301003","https://openalex.org/W4283459170","https://openalex.org/W4220949352","https://openalex.org/W4229014887","https://openalex.org/W4229067106","https://openalex.org/W281791438"],"abstract_inverted_index":{"Social":[0],"media":[1],"content":[2,43,60,127,163],"can":[3,45],"present":[4],"a":[5,79,92,119,173],"number":[6],"of":[7,33,54,68,78,101,172,192,195],"threats,":[8],"including":[9],"misinformation":[10,184],"and":[11,26,56,107,136,143,185,199],"hate":[12,186],"speech":[13,187],"towards":[14],"specific":[15],"demographic":[16],"groups.":[17],"One":[18],"challenge":[19],"is":[20,164],"to":[21,50,75,140],"effectively":[22],"discriminate":[23],"between":[24],"benign":[25,106,161],"malicious":[27,42,108,125],"posts,":[28],"given":[29],"the":[30,51,69,76,84,99,156,170,190],"massive":[31],"amount":[32],"available":[34],"content.":[35,109],"In":[36,110],"this":[37,111,115],"context,":[38],"predictive":[39],"models":[40,72,139,198],"for":[41,63,104,124],"detection":[44,71],"be":[46],"extremely":[47],"valuable,":[48],"leading":[49],"automatic":[52],"removal":[53],"posts":[55,148,188],"user":[57],"accounts":[58],"or":[59],"being":[61],"flagged":[62],"subsequent":[64],"moderation.":[65],"However,":[66],"some":[67],"existing":[70],"are":[73],"limited":[74],"analysis":[77],"single":[80],"data":[81,103,145],"modality.":[82],"At":[83],"same":[85],"time,":[86],"most":[87],"multi-modal":[88],"approaches":[89],"operate":[90],"in":[91,146,155],"fully":[93,174],"supervised":[94,175],"learning":[95,122,138,197],"setting":[96],"that":[97],"assumes":[98],"availability":[100],"labeled":[102],"both":[105],"paper,":[112],"we":[113],"fill":[114],"gap":[116],"by":[117],"proposing":[118],"multimodal":[120],"one-class":[121,137,196],"approach":[123,130],"online":[126,147,162],"detection.":[128],"Our":[129,177],"leverages":[131],"feature":[132],"extraction,":[133],"dimensionality":[134,200],"reduction,":[135],"analyze":[141],"text":[142],"image":[144],"simultaneously.":[149],"Models":[150],"learn":[151],"their":[152],"decision":[153],"function":[154],"challenging":[157],"scenario":[158],"where":[159],"only":[160],"used":[165],"as":[166],"training":[167],"data,":[168],"overcoming":[169],"limitations":[171],"setting.":[176],"experiments":[178],"with":[179],"two":[180],"real-world":[181],"datasets":[182],"containing":[183],"reveal":[189],"effectiveness":[191],"different":[193],"combinations":[194],"reduction":[201],"techniques.":[202]},"counts_by_year":[{"year":2024,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
