{"id":"https://openalex.org/W4406459060","doi":"https://doi.org/10.1109/bigdata62323.2024.10826052","title":"An Information Reliability Framework for Detecting Misinformation based on Large Language Models","display_name":"An Information Reliability Framework for Detecting Misinformation based on Large Language Models","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4406459060","doi":"https://doi.org/10.1109/bigdata62323.2024.10826052"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata62323.2024.10826052","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10826052","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-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/A5115940125","display_name":"Venkata Sai Prathyush Turaga","orcid":"https://orcid.org/0009-0007-6681-281X"},"institutions":[{"id":"https://openalex.org/I12315562","display_name":"Texas Tech University","ror":"https://ror.org/0405mnx93","country_code":"US","type":"education","lineage":["https://openalex.org/I12315562"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Venkata Sai Prathyush Turaga","raw_affiliation_strings":["Texas Tech University,Department of Computer Science"],"affiliations":[{"raw_affiliation_string":"Texas Tech University,Department of Computer Science","institution_ids":["https://openalex.org/I12315562"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026464816","display_name":"Akbar Siami Namin","orcid":"https://orcid.org/0000-0002-1646-7495"},"institutions":[{"id":"https://openalex.org/I12315562","display_name":"Texas Tech University","ror":"https://ror.org/0405mnx93","country_code":"US","type":"education","lineage":["https://openalex.org/I12315562"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Akbar Siami Namin","raw_affiliation_strings":["Texas Tech University,Department of Computer Science"],"affiliations":[{"raw_affiliation_string":"Texas Tech University,Department of Computer Science","institution_ids":["https://openalex.org/I12315562"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5115940125"],"corresponding_institution_ids":["https://openalex.org/I12315562"],"apc_list":null,"apc_paid":null,"fwci":1.1068,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.86161508,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"3599","last_page":"3608"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11147","display_name":"Misinformation and Its Impacts","score":0.9994999766349792,"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":0.9994999766349792,"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":0.996999979019165,"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":0.9912999868392944,"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/misinformation","display_name":"Misinformation","score":0.8371783494949341},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7814386487007141},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.693963885307312},{"id":"https://openalex.org/keywords/reliability-theory","display_name":"Reliability theory","score":0.4110395312309265},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.38588958978652954},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.38040801882743835},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3209426999092102},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.2236192226409912},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09042155742645264}],"concepts":[{"id":"https://openalex.org/C2776990098","wikidata":"https://www.wikidata.org/wiki/Q13579947","display_name":"Misinformation","level":2,"score":0.8371783494949341},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7814386487007141},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.693963885307312},{"id":"https://openalex.org/C201729545","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability theory","level":3,"score":0.4110395312309265},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.38588958978652954},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.38040801882743835},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3209426999092102},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.2236192226409912},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09042155742645264},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C163164238","wikidata":"https://www.wikidata.org/wiki/Q2737027","display_name":"Failure rate","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata62323.2024.10826052","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10826052","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.6299999952316284,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W2170505850","https://openalex.org/W2741026990","https://openalex.org/W2909195503","https://openalex.org/W2963961878","https://openalex.org/W3027879771","https://openalex.org/W3045683288","https://openalex.org/W4224084922","https://openalex.org/W4229452676","https://openalex.org/W4298178213","https://openalex.org/W4319983294","https://openalex.org/W4385570822","https://openalex.org/W4387968438","https://openalex.org/W4388773237","https://openalex.org/W4391129140","https://openalex.org/W4391620737","https://openalex.org/W4399154003","https://openalex.org/W4399197963","https://openalex.org/W4401042272","https://openalex.org/W6777615688","https://openalex.org/W6792206879","https://openalex.org/W6811704848","https://openalex.org/W6860742665","https://openalex.org/W6868202865"],"related_works":["https://openalex.org/W2033512842","https://openalex.org/W4233600955","https://openalex.org/W4322734194","https://openalex.org/W3116237489","https://openalex.org/W4404996554","https://openalex.org/W2913665393","https://openalex.org/W2369695847","https://openalex.org/W3005535424","https://openalex.org/W2994319598","https://openalex.org/W2047067935"],"abstract_inverted_index":{"Information":[0],"plays":[1],"a":[2,65,118,122,139],"key":[3],"role":[4],"in":[5,106,160],"decision":[6],"making,":[7],"influencing":[8],"others":[9],"and":[10,30,37,44,55,77,99,109,129,148,157,187,216,235],"risk":[11],"assessment.":[12],"However,":[13],"malicious":[14,127],"actors":[15],"often":[16],"falsify":[17],"facts":[18],"to":[19,102,116,121,137],"mislead":[20],"viewers.":[21],"With":[22],"the":[23,42,51,60,94,143,162,197,204],"advent":[24],"of":[25,53],"Generative":[26],"AI":[27],"models,":[28],"creating":[29],"modifying":[31],"information":[32,156],"has":[33],"become":[34],"much":[35],"easier":[36],"more":[38],"accessible,":[39],"significantly":[40],"reducing":[41],"time":[43],"effort":[45],"required":[46],"for":[47,88,142,222],"attackers.":[48],"To":[49,151],"address":[50],"challenges":[52],"misinformation":[54],"disinformation,":[56,108],"this":[57],"paper":[58],"presents":[59],"\"Information":[61],"Reliability":[62],"Framework":[63],"(IRF),\"":[64],"detection":[66],"framework":[67,163,173],"built":[68],"with":[69,135,179,193],"DarkBERT":[70,90,115],"(a":[71,79],"dark":[72],"web-focused":[73],"language":[74,81],"model)":[75],"[1]":[76],"LLaMA-3.1":[78,136,178],"large":[80],"model),":[82],"which":[83,131],"incorporates":[84],"real-time":[85,165],"web":[86,166],"data":[87,167],"validation.":[89],"was":[91,174],"fine-tuned":[92],"using":[93,168,181],"FEVER":[95],"dataset":[96],"(Fact":[97],"Extraction":[98],"VERification)":[100],"[2]":[101],"enhance":[103],"its":[104,146,194],"efficiency":[105],"misinformation,":[107],"fact-checking":[110],"tasks.":[111],"This":[112],"fine-tuning":[113],"enables":[114],"assign":[117],"reliability":[119],"score":[120],"given":[123],"statement":[124],"by":[125,191],"analyzing":[126],"keywords":[128],"contexts,":[130],"is":[132],"then":[133],"combined":[134],"generate":[138],"detailed":[140],"explanation":[141],"user,":[144],"leveraging":[145],"knowledge":[147],"logical":[149],"reasoning.":[150],"minimize":[152],"reliance":[153],"on":[154],"outdated":[155],"reduce":[158],"hallucinations":[159],"LLaMA-3.1,":[161],"integrates":[164],"Retrieval-Augmented":[169],"Generation":[170],"(RAG).":[171],"The":[172,200],"evaluated":[175],"alongside":[176],"standalone":[177],"RAG":[180],"two":[182],"synthetic":[183],"datasets:":[184],"generic":[185],"statements":[186],"DarkBERT-specific":[188],"statements,":[189],"generated":[190],"ChatGPT-4o":[192],"latest":[195],"\"search":[196],"web\"":[198],"feature.":[199],"evaluation":[201],"showed":[202],"that":[203],"IRF":[205],"provided":[206],"promising":[207],"results":[208],"across":[209],"metrics":[210],"such":[211],"as":[212],"accuracy,":[213],"precision,":[214],"recall,":[215],"F1":[217],"score,":[218],"making":[219],"it":[220],"effective":[221],"validating":[223],"text":[224],"from":[225],"various":[226],"sources,":[227],"including":[228],"social":[229],"media,":[230],"emails,":[231],"articles,":[232],"messages,":[233],"websites,":[234],"blogs.":[236]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}