{"id":"https://openalex.org/W4415428945","doi":"https://doi.org/10.3233/faia250858","title":"Knowledge-Driven Bayesian Uncertainty Quantification for Reliable Fake News Detection","display_name":"Knowledge-Driven Bayesian Uncertainty Quantification for Reliable Fake News Detection","publication_year":2025,"publication_date":"2025-10-21","ids":{"openalex":"https://openalex.org/W4415428945","doi":"https://doi.org/10.3233/faia250858"},"language":null,"primary_location":{"id":"doi:10.3233/faia250858","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia250858","pdf_url":null,"source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.3233/faia250858","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5116626729","display_name":"Julia Puczy\u0144ska","orcid":null},"institutions":[{"id":"https://openalex.org/I4210128244","display_name":"Institute of Biochemistry and Biophysics, Polish Academy of Sciences","ror":"https://ror.org/034tvp782","country_code":"PL","type":"facility","lineage":["https://openalex.org/I4210128244","https://openalex.org/I99542240"]},{"id":"https://openalex.org/I4210166577","display_name":"Narodowy Instytut Lek\u00f3w","ror":"https://ror.org/05m2pwn60","country_code":"PL","type":"facility","lineage":["https://openalex.org/I4210166577"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Julia Puczy\u0144ska","raw_affiliation_strings":["IDEAS NCBR Sp. z o.o., 69 Chmielna Street, 00-801 Warsaw, Poland","IPPT PAN, Pawi\u0144skiego 5B, 02-106 Warsaw, Poland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IDEAS NCBR Sp. z o.o., 69 Chmielna Street, 00-801 Warsaw, Poland","institution_ids":["https://openalex.org/I4210166577"]},{"raw_affiliation_string":"IPPT PAN, Pawi\u0144skiego 5B, 02-106 Warsaw, Poland","institution_ids":["https://openalex.org/I4210128244"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057697626","display_name":"Youcef Djenouri","orcid":"https://orcid.org/0000-0003-0135-7450"},"institutions":[{"id":"https://openalex.org/I2801380234","display_name":"University of South-Eastern Norway","ror":"https://ror.org/05ecg5h20","country_code":"NO","type":"education","lineage":["https://openalex.org/I2801380234"]},{"id":"https://openalex.org/I4210107808","display_name":"NORCE Research AS","ror":"https://ror.org/02gagpf75","country_code":"NO","type":"facility","lineage":["https://openalex.org/I4210107808"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Youcef Djenouri","raw_affiliation_strings":["Norwegian Research Center (NORCE), Oslo, Norway","University of South-Eastern Norway (USN), Post office box 4, 3199 Borre, Norway"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Norwegian Research Center (NORCE), Oslo, Norway","institution_ids":["https://openalex.org/I4210107808"]},{"raw_affiliation_string":"University of South-Eastern Norway (USN), Post office box 4, 3199 Borre, Norway","institution_ids":["https://openalex.org/I2801380234"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064371005","display_name":"Micha\u0142 Bizo\u0144","orcid":"https://orcid.org/0000-0001-6576-4245"},"institutions":[{"id":"https://openalex.org/I4210166577","display_name":"Narodowy Instytut Lek\u00f3w","ror":"https://ror.org/05m2pwn60","country_code":"PL","type":"facility","lineage":["https://openalex.org/I4210166577"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Micha\u0142 Bizo\u0144","raw_affiliation_strings":["IDEAS NCBR Sp. z o.o., 69 Chmielna Street, 00-801 Warsaw, Poland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IDEAS NCBR Sp. z o.o., 69 Chmielna Street, 00-801 Warsaw, Poland","institution_ids":["https://openalex.org/I4210166577"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025396810","display_name":"Tomasz Michalak","orcid":"https://orcid.org/0000-0002-5288-0324"},"institutions":[{"id":"https://openalex.org/I4210150735","display_name":"IDEA of Development Foundation","ror":"https://ror.org/045embs06","country_code":"PL","type":"other","lineage":["https://openalex.org/I4210150735"]},{"id":"https://openalex.org/I4654613","display_name":"University of Warsaw","ror":"https://ror.org/039bjqg32","country_code":"PL","type":"education","lineage":["https://openalex.org/I4654613"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Tomasz Michalak","raw_affiliation_strings":["IDEAS Research Institute, 27 Kr\u00f3lewska, 00-060 Warsaw, Poland","Institute of Informatics, Warsaw University, Banacha 2, 02-097, Warsaw, Poland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IDEAS Research Institute, 27 Kr\u00f3lewska, 00-060 Warsaw, Poland","institution_ids":["https://openalex.org/I4210150735"]},{"raw_affiliation_string":"Institute of Informatics, Warsaw University, Banacha 2, 02-097, Warsaw, Poland","institution_ids":["https://openalex.org/I4654613"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025494465","display_name":"Piotr Sankowski","orcid":"https://orcid.org/0000-0002-0907-3754"},"institutions":[{"id":"https://openalex.org/I4210142160","display_name":"Papieski Wydzia\u0142 Teologiczny w Warszawie","ror":"https://ror.org/04fh2kz81","country_code":"PL","type":"education","lineage":["https://openalex.org/I4210142160"]},{"id":"https://openalex.org/I4210150735","display_name":"IDEA of Development Foundation","ror":"https://ror.org/045embs06","country_code":"PL","type":"other","lineage":["https://openalex.org/I4210150735"]},{"id":"https://openalex.org/I4654613","display_name":"University of Warsaw","ror":"https://ror.org/039bjqg32","country_code":"PL","type":"education","lineage":["https://openalex.org/I4654613"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Piotr Sankowski","raw_affiliation_strings":["IDEAS Research Institute, 27 Kr\u00f3lewska, 00-060 Warsaw, Poland","Institute of Informatics, Warsaw University, Banacha 2, 02-097, Warsaw, Poland","MIM Solutions, 47 \u015awieradowska, 02-662 Warsaw, Poland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IDEAS Research Institute, 27 Kr\u00f3lewska, 00-060 Warsaw, Poland","institution_ids":["https://openalex.org/I4210150735"]},{"raw_affiliation_string":"Institute of Informatics, Warsaw University, Banacha 2, 02-097, Warsaw, Poland","institution_ids":["https://openalex.org/I4654613"]},{"raw_affiliation_string":"MIM Solutions, 47 \u015awieradowska, 02-662 Warsaw, Poland","institution_ids":["https://openalex.org/I4210142160"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.57519099,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11147","display_name":"Misinformation and Its Impacts","score":0.9994000196456909,"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":0.9994000196456909,"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/T11644","display_name":"Spam and Phishing Detection","score":0.9944999814033508,"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"}},{"id":"https://openalex.org/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9787999987602234,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/interpretability","display_name":"Interpretability","score":0.8127999901771545},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.6919000148773193},{"id":"https://openalex.org/keywords/uncertainty-quantification","display_name":"Uncertainty quantification","score":0.6238999962806702},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5982999801635742},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5978000164031982},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.5063999891281128},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.4961000084877014},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.46540001034736633},{"id":"https://openalex.org/keywords/measurement-uncertainty","display_name":"Measurement uncertainty","score":0.4341000020503998},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4284999966621399}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.8127999901771545},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.699400007724762},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6919000148773193},{"id":"https://openalex.org/C32230216","wikidata":"https://www.wikidata.org/wiki/Q7882499","display_name":"Uncertainty quantification","level":2,"score":0.6238999962806702},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5982999801635742},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5978000164031982},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.536899983882904},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5139999985694885},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.5063999891281128},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.4961000084877014},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46799999475479126},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.46540001034736633},{"id":"https://openalex.org/C137209882","wikidata":"https://www.wikidata.org/wiki/Q1403517","display_name":"Measurement uncertainty","level":2,"score":0.4341000020503998},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4284999966621399},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.4027999937534332},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.3846000134944916},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.35409998893737793},{"id":"https://openalex.org/C177803969","wikidata":"https://www.wikidata.org/wiki/Q29205","display_name":"Uncertainty analysis","level":2,"score":0.35269999504089355},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.34769999980926514},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.3292999863624573},{"id":"https://openalex.org/C917703","wikidata":"https://www.wikidata.org/wiki/Q7239668","display_name":"Predictive inference","level":5,"score":0.3271999955177307},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.30480000376701355},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.29649999737739563},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.29190000891685486},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.27250000834465027},{"id":"https://openalex.org/C94361409","wikidata":"https://www.wikidata.org/wiki/Q7882500","display_name":"Uncertainty reduction theory","level":2,"score":0.2676999866962433},{"id":"https://openalex.org/C2776145597","wikidata":"https://www.wikidata.org/wiki/Q25339462","display_name":"Dropout (neural networks)","level":2,"score":0.267300009727478},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.26089999079704285},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.2558000087738037},{"id":"https://openalex.org/C101112237","wikidata":"https://www.wikidata.org/wiki/Q4874481","display_name":"Bayesian statistics","level":4,"score":0.25290000438690186},{"id":"https://openalex.org/C2779756789","wikidata":"https://www.wikidata.org/wiki/Q28549308","display_name":"Fake news","level":2,"score":0.2517000138759613}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/faia250858","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia250858","pdf_url":null,"source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"}],"best_oa_location":{"id":"doi:10.3233/faia250858","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia250858","pdf_url":null,"source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,43,87],"pervasive":[1],"dissemination":[2],"of":[3,81,129,136],"fake":[4,31],"news":[5,32,85],"presents":[6],"significant":[7],"challenges":[8],"to":[9,55,107],"societal":[10],"well-being":[11],"and":[12,76,95,103,124,133],"informed":[13],"decision-making,":[14],"necessitating":[15],"robust":[16],"detection":[17],"mechanisms":[18],"with":[19,37,116],"calibrated":[20],"uncertainty":[21,35],"measures.":[22],"This":[23],"paper":[24],"proposes":[25],"a":[26,38,64],"novel":[27],"hybrid":[28],"framework":[29],"for":[30],"detection,":[33],"integrating":[34],"quantification":[36],"domain-specific":[39],"Knowledge":[40],"Base":[41],"approach.":[42],"BANED":[44,137],"knowledge":[45],"base":[46],"models":[47],"word-level":[48,113],"probabilistic":[49,114],"significance,":[50],"leveraging":[51],"statistical":[52],"support":[53],"metrics":[54,62],"assess":[56],"prediction":[57],"uncertainty.":[58],"By":[59],"incorporating":[60],"these":[61],"into":[63],"Bayesian":[65,109],"framework,":[66],"our":[67],"method":[68],"provides":[69],"well-calibrated":[70],"predictive":[71],"distributions,":[72],"offering":[73],"enhanced":[74],"interpretability":[75],"robustness":[77],"in":[78],"the":[79,93,126],"presence":[80],"ambiguous":[82],"or":[83],"conflicting":[84],"data.":[86],"proposed":[88],"approach":[89],"is":[90],"evaluated":[91],"on":[92],"FakeNewsNet":[94],"ISOT":[96],"Fake":[97],"News":[98],"datasets,":[99],"demonstrating":[100],"competitive":[101],"accuracy":[102],"superior":[104],"reliability":[105],"compared":[106],"state-of-the-art":[108],"inference":[110],"techniques.":[111],"Combining":[112],"significance":[115],"Monte":[117],"Carlo":[118],"Dropout":[119],"decreases":[120],"mean":[121],"calibration":[122],"error":[123],"narrows":[125],"interquartile":[127],"range":[128],"predictions.":[130],"Full":[131],"code":[132],"supplementary":[134],"materials":[135],"might":[138],"be":[139],"found":[140],"at":[141],"https://github.com/micbizon/BANED.":[142]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-24T00:00:00"}
