{"id":"https://openalex.org/W4307566948","doi":"https://doi.org/10.1017/s1351324922000456","title":"Towards universal methods for fake news detection","display_name":"Towards universal methods for fake news detection","publication_year":2022,"publication_date":"2022-10-26","ids":{"openalex":"https://openalex.org/W4307566948","doi":"https://doi.org/10.1017/s1351324922000456"},"language":"en","primary_location":{"id":"doi:10.1017/s1351324922000456","is_oa":false,"landing_page_url":"https://doi.org/10.1017/s1351324922000456","pdf_url":null,"source":{"id":"https://openalex.org/S18088403","display_name":"Natural Language Engineering","issn_l":"1351-3249","issn":["1351-3249","1469-8110"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311721","host_organization_name":"Cambridge University Press","host_organization_lineage":["https://openalex.org/P4310311721","https://openalex.org/P4310311702"],"host_organization_lineage_names":["Cambridge University Press","University of Cambridge"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Natural Language Engineering","raw_type":"journal-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/A5066155920","display_name":"Maria Pszona","orcid":"https://orcid.org/0000-0003-3557-4998"},"institutions":[{"id":"https://openalex.org/I4210128738","display_name":"Samsung (Poland)","ror":"https://ror.org/0381acm07","country_code":"PL","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210128738"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Maria Pszona","raw_affiliation_strings":["Samsung R&D Institute Poland, pl. Europejski 1, 00-844 Warsaw, Poland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Samsung R&D Institute Poland, pl. Europejski 1, 00-844 Warsaw, Poland","institution_ids":["https://openalex.org/I4210128738"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033747222","display_name":"Maria Janicka","orcid":null},"institutions":[{"id":"https://openalex.org/I4210128738","display_name":"Samsung (Poland)","ror":"https://ror.org/0381acm07","country_code":"PL","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210128738"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Maria Janicka","raw_affiliation_strings":["Samsung R&D Institute Poland, pl. Europejski 1, 00-844 Warsaw, Poland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Samsung R&D Institute Poland, pl. Europejski 1, 00-844 Warsaw, Poland","institution_ids":["https://openalex.org/I4210128738"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029910521","display_name":"Grzegorz Wojdyga","orcid":"https://orcid.org/0000-0003-4880-5142"},"institutions":[{"id":"https://openalex.org/I4210087266","display_name":"Institute of Computer Science","ror":"https://ror.org/003fvp964","country_code":"PL","type":"facility","lineage":["https://openalex.org/I4210087266","https://openalex.org/I99542240"]},{"id":"https://openalex.org/I99542240","display_name":"Polish Academy of Sciences","ror":"https://ror.org/01dr6c206","country_code":"PL","type":"government","lineage":["https://openalex.org/I99542240"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Grzegorz Wojdyga","raw_affiliation_strings":["Institute of Computer Science Polish Academy of Sciences, ul. Jana Kazimierza 5, 01-248 Warszawa, Poland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computer Science Polish Academy of Sciences, ul. Jana Kazimierza 5, 01-248 Warszawa, Poland","institution_ids":["https://openalex.org/I99542240","https://openalex.org/I4210087266"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000658598","display_name":"Aleksander Wawer","orcid":"https://orcid.org/0000-0002-7081-9797"},"institutions":[{"id":"https://openalex.org/I4210087266","display_name":"Institute of Computer Science","ror":"https://ror.org/003fvp964","country_code":"PL","type":"facility","lineage":["https://openalex.org/I4210087266","https://openalex.org/I99542240"]},{"id":"https://openalex.org/I4210128738","display_name":"Samsung (Poland)","ror":"https://ror.org/0381acm07","country_code":"PL","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210128738"]},{"id":"https://openalex.org/I99542240","display_name":"Polish Academy of Sciences","ror":"https://ror.org/01dr6c206","country_code":"PL","type":"government","lineage":["https://openalex.org/I99542240"]}],"countries":["PL"],"is_corresponding":true,"raw_author_name":"Aleksander Wawer","raw_affiliation_strings":["Institute of Computer Science Polish Academy of Sciences, ul. Jana Kazimierza 5, 01-248 Warszawa, Poland","Samsung R&D Institute Poland, pl. Europejski 1, 00-844 Warsaw, Poland"],"raw_orcid":"https://orcid.org/0000-0002-7081-9797","affiliations":[{"raw_affiliation_string":"Institute of Computer Science Polish Academy of Sciences, ul. Jana Kazimierza 5, 01-248 Warszawa, Poland","institution_ids":["https://openalex.org/I99542240","https://openalex.org/I4210087266"]},{"raw_affiliation_string":"Samsung R&D Institute Poland, pl. Europejski 1, 00-844 Warsaw, Poland","institution_ids":["https://openalex.org/I4210128738"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5000658598"],"corresponding_institution_ids":["https://openalex.org/I4210087266","https://openalex.org/I4210128738","https://openalex.org/I99542240"],"apc_list":null,"apc_paid":null,"fwci":0.7924,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.80553576,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"29","issue":"4","first_page":"1004","last_page":"1042"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11147","display_name":"Misinformation and Its Impacts","score":1.0,"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":1.0,"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":0.9970999956130981,"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/T10028","display_name":"Topic Modeling","score":0.9968000054359436,"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":0.8684070110321045},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6331719160079956},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5638761520385742},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.5593321323394775},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5443927049636841},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.5255288481712341},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5245616436004639},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5182271003723145},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.5019128322601318},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.48142358660697937},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4803817868232727},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature engineering","score":0.46694648265838623},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.4599548578262329},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.45621222257614136},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.44526875019073486},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.4190804362297058},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.26987507939338684},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.08455395698547363}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8684070110321045},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6331719160079956},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5638761520385742},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.5593321323394775},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5443927049636841},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.5255288481712341},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5245616436004639},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5182271003723145},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.5019128322601318},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.48142358660697937},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4803817868232727},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.46694648265838623},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.4599548578262329},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.45621222257614136},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.44526875019073486},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.4190804362297058},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.26987507939338684},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.08455395698547363},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"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/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1017/s1351324922000456","is_oa":false,"landing_page_url":"https://doi.org/10.1017/s1351324922000456","pdf_url":null,"source":{"id":"https://openalex.org/S18088403","display_name":"Natural Language Engineering","issn_l":"1351-3249","issn":["1351-3249","1469-8110"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311721","host_organization_name":"Cambridge University Press","host_organization_lineage":["https://openalex.org/P4310311721","https://openalex.org/P4310311702"],"host_organization_lineage_names":["Cambridge University Press","University of Cambridge"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Natural Language Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.550000011920929}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":63,"referenced_works":["https://openalex.org/W133394232","https://openalex.org/W1565327149","https://openalex.org/W1565746575","https://openalex.org/W1882958252","https://openalex.org/W1967390364","https://openalex.org/W2048587526","https://openalex.org/W2082291422","https://openalex.org/W2091034860","https://openalex.org/W2092939357","https://openalex.org/W2101234009","https://openalex.org/W2104068492","https://openalex.org/W2114524997","https://openalex.org/W2117334662","https://openalex.org/W2149466042","https://openalex.org/W2154053567","https://openalex.org/W2157134953","https://openalex.org/W2162651021","https://openalex.org/W2250539671","https://openalex.org/W2281492572","https://openalex.org/W2410465342","https://openalex.org/W2582561810","https://openalex.org/W2593408211","https://openalex.org/W2604264634","https://openalex.org/W2759820691","https://openalex.org/W2773963565","https://openalex.org/W2790166049","https://openalex.org/W2805394970","https://openalex.org/W2890801081","https://openalex.org/W2891177506","https://openalex.org/W2896457183","https://openalex.org/W2962739339","https://openalex.org/W2962897020","https://openalex.org/W2963416784","https://openalex.org/W2963961878","https://openalex.org/W2964060837","https://openalex.org/W2970379526","https://openalex.org/W2970716846","https://openalex.org/W2978583898","https://openalex.org/W2978872346","https://openalex.org/W2988718760","https://openalex.org/W2988787701","https://openalex.org/W3004623877","https://openalex.org/W3029439886","https://openalex.org/W3031781733","https://openalex.org/W3034020579","https://openalex.org/W3045987077","https://openalex.org/W3090760060","https://openalex.org/W3099977667","https://openalex.org/W3101244349","https://openalex.org/W3107298362","https://openalex.org/W3138953784","https://openalex.org/W3147509388","https://openalex.org/W3164693331","https://openalex.org/W3191286626","https://openalex.org/W4252684946","https://openalex.org/W6605422000","https://openalex.org/W6675354045","https://openalex.org/W6677069268","https://openalex.org/W6682388183","https://openalex.org/W6745831770","https://openalex.org/W6748312029","https://openalex.org/W6761334744","https://openalex.org/W6763240421"],"related_works":["https://openalex.org/W2112471020","https://openalex.org/W1612029326","https://openalex.org/W3200179079","https://openalex.org/W3185194050","https://openalex.org/W4324137389","https://openalex.org/W1772447446","https://openalex.org/W2789277863","https://openalex.org/W2223152534","https://openalex.org/W4298881487","https://openalex.org/W3105729093"],"abstract_inverted_index":{"Abstract":[0],"Fake":[1],"news":[2,26],"detection":[3,27],"is":[4],"an":[5],"emerging":[6],"topic":[7],"that":[8,75,187],"has":[9],"attracted":[10],"a":[11,29,71,94,114,132,137],"lot":[12],"of":[13,36,62,70,96,139,190,216,226],"attention":[14],"among":[15],"researchers":[16],"and":[17,102,152,154,171,180,193],"in":[18,84,113,131],"the":[19,34,48,68,124,176,207,219,223],"industry.":[20],"This":[21],"paper":[22,120],"focuses":[23,121],"on":[24,33,58,79,99,105,122,159],"fake":[25],"as":[28,44],"text":[30],"classification":[31,97],"problem:":[32],"basis":[35],"five":[37],"publicly":[38],"available":[39],"corpora":[40],"with":[41],"documents":[42],"labeled":[43],"true":[45],"or":[46],"fake,":[47],"task":[49],"was":[50,65,228],"to":[51,66,89,128,146,166],"automatically":[52],"distinguish":[53],"both":[54],"classes":[55],"without":[56],"relying":[57],"fact-checking.":[59],"The":[60],"aim":[61],"our":[63,85],"research":[64],"test":[67],"feasibility":[69],"universal":[72],"model:":[73],"one":[74,100],"produces":[76],"satisfactory":[77],"results":[78],"all":[80,213],"data":[81,147],"sets":[82],"tested":[83],"article.":[86],"We":[87,135],"attempted":[88],"do":[90],"so":[91],"by":[92,230],"training":[93],"set":[95,148],"models":[98],"collection":[101],"testing":[103],"them":[104],"another.":[106],"As":[107],"it":[108],"turned":[109],"out,":[110],"this":[111,119],"resulted":[112],"sharp":[115],"performance":[116],"degradation.":[117],"Therefore,":[118],"finding":[123],"most":[125],"effective":[126],"approach":[127],"utilizing":[129],"information":[130],"transferable":[133],"manner.":[134],"examined":[136],"variety":[138],"methods:":[140],"feature":[141,168,195,204],"selection,":[142],"machine":[143],"learning":[144,156],"approaches":[145,157],"shift":[149],"(instance":[150],"re-weighting":[151],"projection-based),":[153],"deep":[155],"based":[158],"domain":[160,220],"transfer.":[161],"These":[162],"methods":[163,192],"were":[164],"applied":[165],"various":[167],"spaces:":[169],"linguistic":[170,202],"psycholinguistic,":[172],"embeddings":[173],"obtained":[174],"from":[175],"Universal":[177],"Sentence":[178],"Encoder,":[179],"GloVe":[181],"embeddings.":[182],"A":[183],"detailed":[184],"analysis":[185],"showed":[186],"some":[188],"combinations":[189],"these":[191],"selected":[194],"spaces":[196],"bring":[197],"significant":[198],"improvements.":[199],"When":[200],"using":[201],"data,":[203],"selection":[205],"yielded":[206],"best":[208],"overall":[209],"mean":[210],"improvement":[211,225],"(across":[212],"train-test":[214],"pairs)":[215],"4%.":[217],"Among":[218],"adaptation":[221],"methods,":[222],"greatest":[224],"3%":[227],"achieved":[229],"subspace":[231],"alignment.":[232]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2025-10-10T00:00:00"}