{"id":"https://openalex.org/W7225638681","doi":"https://doi.org/10.1038/s41598-026-80297-4","title":"Feature guided prompting distorts synthetic fake news corpora without improving detection","display_name":"Feature guided prompting distorts synthetic fake news corpora without improving detection","publication_year":2026,"publication_date":"2026-11-09","ids":{"openalex":"https://openalex.org/W7225638681","doi":"https://doi.org/10.1038/s41598-026-80297-4"},"language":"en","primary_location":{"id":"doi:10.1038/s41598-026-80297-4","doi":"https://doi.org/10.1038/s41598-026-80297-4","is_oa":true,"landing_page_url":"https://doi.org/10.1038/s41598-026-80297-4","pdf_url":"https://www.nature.com/articles/s41598-026-80297-4_reference.pdf","source":{"id":"https://openalex.org/S196734849","display_name":"Scientific Reports","issn_l":"2045-2322","issn":["2045-2322"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","dongbi-c","doyens","jufo-1","ki-jl-1","medline","norway-1","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319908","host_organization_name":"Nature Portfolio","host_organization_lineage":["https://openalex.org/P4310319908","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Nature Portfolio","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientific Reports","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.nature.com/articles/s41598-026-80297-4_reference.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5051422114","display_name":"Sharyar Wani","orcid":"https://orcid.org/0000-0001-6812-0066","observed_orcids":["https://orcid.org/0000-0001-6812-0066"]},"institutions":[{"id":"https://openalex.org/I4164984","display_name":"International Islamic University Malaysia","ror":"https://ror.org/03s9hs139","country_code":"MY","type":"education","lineage":["https://openalex.org/I4164984"]}],"countries":["MY"],"is_corresponding":true,"raw_author_name":"Sharyar Wani","raw_affiliation_strings":["Department of Computer Science, Kulliyyah of Information and Communication Technology, International Islamic University Malaysia, Kuala Lumpur, 53100, Malaysia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Kulliyyah of Information and Communication Technology, International Islamic University Malaysia, Kuala Lumpur, 53100, Malaysia","institution_ids":["https://openalex.org/I4164984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020243793","display_name":"Hewa Majeed Zangana","orcid":"https://orcid.org/0000-0001-7909-254X","observed_orcids":["https://orcid.org/0000-0001-7909-254X"]},"institutions":[{"id":"https://openalex.org/I4210124331","display_name":"Duhok Polytechnic University","ror":"https://ror.org/024kjbt21","country_code":"IQ","type":"education","lineage":["https://openalex.org/I4210124331"]}],"countries":["IQ"],"is_corresponding":false,"raw_author_name":"Hewa Majeed Zangana","raw_affiliation_strings":["Duhok Technical College, Duhok Polytechnic University, Duhok, Kurdistan Region , 42001, Iraq"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Duhok Technical College, Duhok Polytechnic University, Duhok, Kurdistan Region , 42001, Iraq","institution_ids":["https://openalex.org/I4210124331"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013837562","display_name":"Yonis Gulzar","orcid":"https://orcid.org/0000-0002-6515-1569","observed_orcids":["https://orcid.org/0000-0002-6515-1569"]},"institutions":[{"id":"https://openalex.org/I4626487","display_name":"King Faisal University","ror":"https://ror.org/00dn43547","country_code":"SA","type":"education","lineage":["https://openalex.org/I4626487"]}],"countries":["SA"],"is_corresponding":true,"raw_author_name":"Yonis Gulzar","raw_affiliation_strings":["Department of Management Information Systems, College of Business Administration, King Faisal University, Al-Ahsa, 31982, Saudi Arabia"],"raw_orcid":"https://orcid.org/0000-0002-6515-1569","affiliations":[{"raw_affiliation_string":"Department of Management Information Systems, College of Business Administration, King Faisal University, Al-Ahsa, 31982, Saudi Arabia","institution_ids":["https://openalex.org/I4626487"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029763877","display_name":"Mohannad Alkanan","orcid":"https://orcid.org/0000-0003-3736-7749","observed_orcids":["https://orcid.org/0000-0003-3736-7749"]},"institutions":[{"id":"https://openalex.org/I4626487","display_name":"King Faisal University","ror":"https://ror.org/00dn43547","country_code":"SA","type":"education","lineage":["https://openalex.org/I4626487"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Mohannad Alkanan","raw_affiliation_strings":["Department of Management Information Systems, College of Business Administration, King Faisal University, Al-Ahsa, 31982, Saudi Arabia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Management Information Systems, College of Business Administration, King Faisal University, Al-Ahsa, 31982, Saudi Arabia","institution_ids":["https://openalex.org/I4626487"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5013837562","https://openalex.org/A5051422114"],"corresponding_institution_ids":["https://openalex.org/I4164984","https://openalex.org/I4626487"],"apc_list":{"value":2690,"currency":"USD","value_usd":2690},"apc_paid":{"value":2690,"currency":"USD","value_usd":2690},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"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":0.9976000189781189,"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":0.9976000189781189,"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":0.0013000000035390258,"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/T11644","display_name":"Spam and Phishing Detection","score":0.00019999999494757503,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/fake-news-detection","display_name":"fake news detection","score":0.9160000085830688},{"id":"https://openalex.org/keywords/synthetic-training-data","display_name":"synthetic training data","score":0.703000009059906},{"id":"https://openalex.org/keywords/prompt-engineering","display_name":"prompt engineering","score":0.6589999794960022},{"id":"https://openalex.org/keywords/class-imbalance","display_name":"class imbalance","score":0.5960000157356262},{"id":"https://openalex.org/keywords/headline-generation","display_name":"headline generation","score":0.5389999747276306},{"id":"https://openalex.org/keywords/equivalence-testing","display_name":"equivalence testing","score":0.5429999828338623},{"id":"https://openalex.org/keywords/oversampling","display_name":"oversampling","score":0.4740000069141388},{"id":"https://openalex.org/keywords/qwen2-5-7b-instruct","display_name":"Qwen2.5-7B-Instruct","score":0.7570000290870667}],"concepts":[{"id":"https://openalex.org/C2778689934","wikidata":"https://www.wikidata.org/wiki/Q1313396","display_name":"Headline","level":2,"score":0.7037000060081482},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6758000254631042},{"id":"https://openalex.org/C2780069185","wikidata":"https://www.wikidata.org/wiki/Q7977945","display_name":"Equivalence (formal languages)","level":2,"score":0.6726999878883362},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5325999855995178},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4763999879360199},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.45809999108314514},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4546000063419342},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.43860000371932983},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.4339999854564667},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.40560001134872437},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.4004000127315521},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.358599990606308},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.35030001401901245},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3427000045776367},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.3310999870300293},{"id":"https://openalex.org/C194051981","wikidata":"https://www.wikidata.org/wiki/Q1337691","display_name":"Economic shortage","level":3,"score":0.32580000162124634},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3125},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.2973000109195709},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2921000123023987},{"id":"https://openalex.org/C2777044963","wikidata":"https://www.wikidata.org/wiki/Q5384707","display_name":"Equivalence class (music)","level":2,"score":0.29030001163482666},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.27390000224113464},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.27149999141693115},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.26179999113082886},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26159998774528503},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.2531000077724457}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1038/s41598-026-80297-4","doi":"https://doi.org/10.1038/s41598-026-80297-4","is_oa":true,"landing_page_url":"https://doi.org/10.1038/s41598-026-80297-4","pdf_url":"https://www.nature.com/articles/s41598-026-80297-4_reference.pdf","source":{"id":"https://openalex.org/S196734849","display_name":"Scientific Reports","issn_l":"2045-2322","issn":["2045-2322"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","dongbi-c","doyens","jufo-1","ki-jl-1","medline","norway-1","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319908","host_organization_name":"Nature Portfolio","host_organization_lineage":["https://openalex.org/P4310319908","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Nature Portfolio","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientific Reports","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1038/s41598-026-80297-4","doi":"https://doi.org/10.1038/s41598-026-80297-4","is_oa":true,"landing_page_url":"https://doi.org/10.1038/s41598-026-80297-4","pdf_url":"https://www.nature.com/articles/s41598-026-80297-4_reference.pdf","source":{"id":"https://openalex.org/S196734849","display_name":"Scientific Reports","issn_l":"2045-2322","issn":["2045-2322"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","dongbi-c","doyens","jufo-1","ki-jl-1","medline","norway-1","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319908","host_organization_name":"Nature Portfolio","host_organization_lineage":["https://openalex.org/P4310319908","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Nature Portfolio","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientific Reports","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322804","display_name":"Deanship of Scientific Research, King Faisal University","ror":"https://ror.org/00dn43547"},{"id":"https://openalex.org/F4320331156","display_name":"King Faisal University","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7225638681.pdf","grobid_xml":"https://content.openalex.org/works/W7225638681.grobid-xml"},"referenced_works_count":26,"referenced_works":["https://openalex.org/W2742330194","https://openalex.org/W2759820691","https://openalex.org/W2791544114","https://openalex.org/W3162734203","https://openalex.org/W3198867954","https://openalex.org/W4226400622","https://openalex.org/W4288079542","https://openalex.org/W4295846679","https://openalex.org/W4403104761","https://openalex.org/W4403826407","https://openalex.org/W4404349631","https://openalex.org/W4408500716","https://openalex.org/W4409550942","https://openalex.org/W4410245843","https://openalex.org/W4412444947","https://openalex.org/W4412736631","https://openalex.org/W4412945164","https://openalex.org/W4413147623","https://openalex.org/W4413472805","https://openalex.org/W4413772162","https://openalex.org/W4415029058","https://openalex.org/W4415798376","https://openalex.org/W7120159797","https://openalex.org/W7154481902","https://openalex.org/W7155651445","https://openalex.org/W7162697120"],"related_works":["https://openalex.org/W7133314533","https://openalex.org/W7120159797","https://openalex.org/W4413772162","https://openalex.org/W4402661084","https://openalex.org/W7162697120","https://openalex.org/W7154481902","https://openalex.org/W4409657122","https://openalex.org/W7213868807","https://openalex.org/W7154175082","https://openalex.org/W4417054932"],"abstract_inverted_index":{"Large":[0],"language":[1],"models":[2],"(LLMs)":[3],"have":[4],"been":[5],"increasingly":[6],"applied":[7],"for":[8,120,140],"generating":[9],"synthetic":[10,51,413],"training":[11],"data":[12,52,72,414],"to":[13,32,50,69],"address":[14],"class":[15],"imbalance":[16],"problems":[17],"in":[18,29,441],"fake":[19,308],"news":[20],"detection.":[21],"Existing":[22],"approaches":[23],"commonly":[24],"apply":[25],"multiple":[26],"stylistic":[27,63,96,169,336],"constraints":[28,49,97,337],"generation":[30,438],"prompts":[31,273],"control":[33],"the":[34,45,87,108,210,214,224,228,239,257,261,266,269,276,285,294,299,312,335,367,397,404,407,432,435],"characteristics":[35],"of":[36,47,223,315,326,378,403,434],"generated":[37,132],"samples":[38,93],"and":[39,94,116,143,158,242,271,303,319,328,359,385,389,406],"evaluate":[40],"their":[41,206],"overall":[42],"compliance.":[43],"However,":[44],"contribution":[46],"individual":[48,168],"augmentation":[53,73,84],"performance":[54,218],"remains":[55],"unclear.":[56],"This":[57],"research":[58],"investigates":[59],"whether":[60],"any":[61],"single":[62],"constraint":[64,170],"is":[65,171,381,399],"necessary":[66],"or":[67],"sufficient":[68],"improve":[70,344],"LLM-based":[71,83],"effectiveness.":[74],"A":[75],"single-feature":[76],"ablation":[77,176],"analysis":[78],"was":[79,105,245],"conducted":[80],"using":[81],"an":[82],"pipeline":[85],"with":[86,145,186,346],"GossipCop\u2013PolitiFact":[88],"headline":[89,437],"dataset":[90],"containing":[91,135],"23,196":[92],"15":[95,175],"adopted":[98],"from":[99],"previous":[100],"research.":[101],"The":[102,163,233,331,350,376],"Qwen2.5-7B-Instruct":[103],"model":[104],"used":[106,119],"as":[107,173,283],"primary":[109,295],"generator":[110,231],"across":[111,227],"26":[112],"prompt":[113,216,226,278,352,369,405,428],"conditions.":[114],"Phi-3.5-mini-instruct":[115],"DeepSeek-R1-Distill-Llama-8B":[117],"were":[118,138],"cross-model":[121],"validation":[122],"on":[123,426],"three":[124,152,191,229],"key":[125],"conditions":[126,244,305],"(full,":[127],"naive,":[128,241,302],"F5-only).":[129],"Three":[130],"independently":[131],"corpora,":[133],"each":[134],"5,000":[136],"headlines,":[137],"produced":[139,196],"every":[141],"condition":[142,289],"evaluated":[144,230,440],"six":[146],"classical":[147],"classifiers":[148],"(30":[149],"seeds":[150,156],"each),":[151,157],"fine-tuned":[153],"transformers":[154],"(3":[155],"one":[159],"zero-shot":[160],"LLM":[161],"classifier.":[162],"results":[164],"indicate":[165,333,411],"that":[166,334,396,412],"no":[167],"necessary,":[172],"all":[174],"settings":[177],"achieved":[178,217,249,306,323],"statistical":[179],"equivalence":[180,184,211],"under":[181],"a":[182,400],"two-one-sided":[183],"test":[185],"\u03b4":[187,220,280],"=":[188,221,281,291],"0.02.":[189],"Although":[190,247],"features":[192],"(F1,":[193],"F7,":[194],"F9)":[195],"statistically":[197],"detectable":[198],"changes":[199],"after":[200],"FDR":[201],"(false":[202],"discovery":[203],"rate)":[204],"correction,":[205],"magnitudes":[207],"remained":[208,259],"within":[209,219,279,431],"margin.":[212,264],"Furthermore,":[213],"F5-only":[215,243,248,304,368],"0.02":[222],"full":[225,277,351],"families.":[232],"maximum":[234],"within-family":[235],"F1":[236,252,309],"difference":[237],"among":[238],"full,":[240,301],"0.0088.":[246],"numerically":[250],"higher":[251,324],"scores":[253,310,325],"than":[254,311,343,423],"naive":[255],"prompting,":[256],"differences":[258],"below":[260],"predefined":[262],"practical":[263],"In":[265,293],"Qwen":[267,300,384],"experiments,":[268],"F6-only":[270],"F12-only":[272],"also":[274],"matched":[275],"0.02,":[282],"did":[284],"F6":[286],"+":[287],"F4":[288],"(\u0394":[290],"\u22120.0037).":[292],"Random":[296,317,321],"Forest":[297,322],"evaluation,":[298],"lower":[307],"no-augmentation":[313],"baseline":[314],"0.6034.":[316],"oversampling":[318],"class-weighted":[320],"0.6324":[327],"0.6452,":[329],"respectively.":[330],"findings":[332,410],"may":[338],"introduce":[339],"distributional":[340,420],"distortions":[341],"rather":[342,422],"alignment":[345,421],"real":[347],"fake-news":[348],"characteristics.":[349],"increased":[353,370],"question":[354],"mark":[355,372],"frequency":[356,373],"by":[357,364,374],"5.3\u00d7":[358],"reduced":[360],"ALL":[361],"CAPS":[362],"usage":[363],"12.5\u00d7,":[365],"while":[366,391],"exclamation":[371],"15\u00d7.":[375],"direction":[377],"question-mark":[379],"distortion":[380],"partly":[382],"model-specific:":[383],"Phi":[386],"over-comply":[387],"(5.34\u00d7":[388],"4.51\u00d7)":[390],"DeepSeek":[392],"under-complies":[393],"(0.66\u00d7),":[394],"confirming":[395],"misalignment":[398],"joint":[401],"property":[402],"generator.":[408],"These":[409],"quality":[415],"evaluation":[416],"should":[417],"consider":[418],"feature-level":[419],"relying":[424],"solely":[425],"aggregate":[427],"compliance,":[429],"particularly":[430],"scope":[433],"English-language":[436],"setting":[439],"this":[442],"study.":[443]},"counts_by_year":[],"updated_date":"2026-11-11T12:16:26.678958","created_date":"2026-11-10T00:00:00"}