{"id":"https://openalex.org/W7124762725","doi":"https://doi.org/10.3390/bdcc10010034","title":"Using Large Language Models to Detect and Debunk Climate Change Misinformation","display_name":"Using Large Language Models to Detect and Debunk Climate Change Misinformation","publication_year":2026,"publication_date":"2026-01-17","ids":{"openalex":"https://openalex.org/W7124762725","doi":"https://doi.org/10.3390/bdcc10010034"},"language":"en","primary_location":{"id":"doi:10.3390/bdcc10010034","is_oa":true,"landing_page_url":"https://doi.org/10.3390/bdcc10010034","pdf_url":"https://www.mdpi.com/2504-2289/10/1/34/pdf?version=1768638130","source":{"id":"https://openalex.org/S4210238752","display_name":"Big Data and Cognitive Computing","issn_l":"2504-2289","issn":["2504-2289"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data and Cognitive Computing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2504-2289/10/1/34/pdf?version=1768638130","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5029242574","display_name":"Zeinab Shahbazi","orcid":"https://orcid.org/0000-0003-1520-1799"},"institutions":[{"id":"https://openalex.org/I193278943","display_name":"Kristianstad University","ror":"https://ror.org/00tkrft03","country_code":"SE","type":"education","lineage":["https://openalex.org/I193278943"]}],"countries":["SE"],"is_corresponding":true,"raw_author_name":"Zeinab Shahbazi","raw_affiliation_strings":["Research Environment of Computer Science (RECS), Kristianstad University, 29188 Kristianstad, Sweden"],"raw_orcid":"https://orcid.org/0000-0003-1520-1799","affiliations":[{"raw_affiliation_string":"Research Environment of Computer Science (RECS), Kristianstad University, 29188 Kristianstad, Sweden","institution_ids":["https://openalex.org/I193278943"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066250635","display_name":"Sara Behnamian","orcid":null},"institutions":[{"id":"https://openalex.org/I124055696","display_name":"University of Copenhagen","ror":"https://ror.org/035b05819","country_code":"DK","type":"education","lineage":["https://openalex.org/I124055696"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Sara Behnamian","raw_affiliation_strings":["Globe Institute, University of Copenhagen, 1350 Copenhagen, Denmark"],"raw_orcid":"https://orcid.org/0000-0003-1115-2504","affiliations":[{"raw_affiliation_string":"Globe Institute, University of Copenhagen, 1350 Copenhagen, Denmark","institution_ids":["https://openalex.org/I124055696"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5029242574"],"corresponding_institution_ids":["https://openalex.org/I193278943"],"apc_list":{"value":1600,"currency":"CHF","value_usd":1782},"apc_paid":{"value":1600,"currency":"CHF","value_usd":1782},"fwci":43.5057,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.99404296,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"10","issue":"1","first_page":"34","last_page":"34"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11147","display_name":"Misinformation and Its Impacts","score":0.8550999760627747,"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":0.8550999760627747,"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/T11488","display_name":"Climate Change Communication and Perception","score":0.06650000065565109,"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/T13910","display_name":"Computational and Text Analysis Methods","score":0.016100000590085983,"subfield":{"id":"https://openalex.org/subfields/3300","display_name":"General Social Sciences"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/misinformation","display_name":"Misinformation","score":0.7307000160217285},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4837999939918518},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.47690001130104065},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.3806999921798706},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.357699990272522},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.33390000462532043},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.31520000100135803},{"id":"https://openalex.org/keywords/computational-linguistics","display_name":"Computational linguistics","score":0.3050999939441681}],"concepts":[{"id":"https://openalex.org/C2776990098","wikidata":"https://www.wikidata.org/wiki/Q13579947","display_name":"Misinformation","level":2,"score":0.7307000160217285},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6929000020027161},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6047999858856201},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5807999968528748},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4837999939918518},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.47690001130104065},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41029998660087585},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.3806999921798706},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.357699990272522},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.33390000462532043},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3174000084400177},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.31520000100135803},{"id":"https://openalex.org/C155092808","wikidata":"https://www.wikidata.org/wiki/Q182557","display_name":"Computational linguistics","level":2,"score":0.3050999939441681},{"id":"https://openalex.org/C132651083","wikidata":"https://www.wikidata.org/wiki/Q7942","display_name":"Climate change","level":2,"score":0.30250000953674316},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.301800012588501},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3000999987125397},{"id":"https://openalex.org/C2779439875","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Natural language understanding","level":3,"score":0.29670000076293945},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.29030001163482666},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.265500009059906},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.2599000036716461},{"id":"https://openalex.org/C166151441","wikidata":"https://www.wikidata.org/wiki/Q4923601","display_name":"Causation","level":2,"score":0.25850000977516174},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.257099986076355}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/bdcc10010034","is_oa":true,"landing_page_url":"https://doi.org/10.3390/bdcc10010034","pdf_url":"https://www.mdpi.com/2504-2289/10/1/34/pdf?version=1768638130","source":{"id":"https://openalex.org/S4210238752","display_name":"Big Data and Cognitive Computing","issn_l":"2504-2289","issn":["2504-2289"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data and Cognitive Computing","raw_type":"journal-article"},{"id":"pmh:oai:pure.atira.dk:openaire_cris_publications/b198a176-3f9e-4fc6-b5cf-76fbfa5ffbf5","is_oa":true,"landing_page_url":"https://researchprofiles.ku.dk/da/publications/b198a176-3f9e-4fc6-b5cf-76fbfa5ffbf5","pdf_url":"https://curis.ku.dk/ws/files/536789658/BDCC-10-00034.pdf","source":{"id":"https://openalex.org/S4306401983","display_name":"Research at the University of Copenhagen (University of Copenhagen)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I124055696","host_organization_name":"University of Copenhagen","host_organization_lineage":["https://openalex.org/I124055696"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Shahbazi , Z & Behnamian , S 2026 , ' Using Large Language Models to Detect and Debunk Climate Change Misinformation ' , Big Data and Cognitive Computing , vol. 10 , no. 1 , 34 . https://doi.org/10.3390/bdcc10010034","raw_type":"article"},{"id":"pmh:oai:doaj.org/article:0ab5fb0b3089491fa29aa0650cb17aad","is_oa":true,"landing_page_url":"https://doaj.org/article/0ab5fb0b3089491fa29aa0650cb17aad","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Big Data and Cognitive Computing, Vol 10, Iss 1, p 34 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/bdcc10010034","is_oa":true,"landing_page_url":"https://doi.org/10.3390/bdcc10010034","pdf_url":"https://www.mdpi.com/2504-2289/10/1/34/pdf?version=1768638130","source":{"id":"https://openalex.org/S4210238752","display_name":"Big Data and Cognitive Computing","issn_l":"2504-2289","issn":["2504-2289"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data and Cognitive Computing","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Climate action","id":"https://metadata.un.org/sdg/13","score":0.6932346820831299}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W7124762725.pdf"},"referenced_works_count":26,"referenced_works":["https://openalex.org/W3135161617","https://openalex.org/W3211024016","https://openalex.org/W4389520670","https://openalex.org/W4389523840","https://openalex.org/W4391610230","https://openalex.org/W4391830434","https://openalex.org/W4392637187","https://openalex.org/W4400364016","https://openalex.org/W4400529431","https://openalex.org/W4401167572","https://openalex.org/W4402670018","https://openalex.org/W4402670143","https://openalex.org/W4402670869","https://openalex.org/W4402671371","https://openalex.org/W4402683855","https://openalex.org/W4402684264","https://openalex.org/W4403577386","https://openalex.org/W4404148389","https://openalex.org/W4404782513","https://openalex.org/W4407932982","https://openalex.org/W4410088531","https://openalex.org/W4410614746","https://openalex.org/W4411120233","https://openalex.org/W4411143199","https://openalex.org/W4411888995","https://openalex.org/W4416036304"],"related_works":[],"abstract_inverted_index":{"The":[0,90,149],"rapid":[1],"spread":[2],"of":[3,39,180,187,255,264,273],"climate":[4,88,181,265],"change":[5],"misinformation":[6,182,266],"across":[7],"digital":[8],"platforms":[9],"undermines":[10],"scientific":[11,164,240],"literacy,":[12],"public":[13],"trust,":[14],"and":[15,25,37,71,82,107,131,140,158,192,217,224,242],"evidence-based":[16],"policy":[17],"action.":[18],"Advances":[19],"in":[20,220],"Natural":[21,122],"Language":[22,27,63,123],"Processing":[23],"(NLP)":[24],"Large":[26,62],"Models":[28],"(LLMs)":[29],"create":[30],"new":[31],"opportunities":[32],"for":[33,87,111,197,270],"automating":[34],"the":[35,170,253],"detection":[36],"correction":[38],"misleading":[40,193],"climate-related":[41],"narratives.":[42],"This":[43],"study":[44],"presents":[45],"a":[46,119],"multi-stage":[47],"system":[48,91],"that":[49,202,233],"employs":[50,152],"state-of-the-art":[51],"large":[52],"language":[53],"models":[54,204],"such":[55,166,210],"as":[56,167,211],"Generative":[57],"Pre-trained":[58],"Transformer":[59],"4":[60],"(GPT-4),":[61],"Model":[64],"Meta":[65],"AI":[66,146],"(LLaMA)":[67],"version":[68],"3":[69],"(LLaMA-3),":[70],"RoBERTa-large":[72],"(Robustly":[73],"optimized":[74],"BERT":[75],"pretraining":[76],"approach":[77],"large)":[78],"to":[79,155,226,246,259],"identify,":[80],"classify,":[81],"generate":[83],"scientifically":[84],"grounded":[85],"corrections":[86],"misinformation.":[89],"integrates":[92],"several":[93],"complementary":[94],"techniques,":[95],"including":[96],"transformer-based":[97],"text":[98],"classification,":[99],"semantic":[100],"similarity":[101],"scoring":[102],"using":[103,129,138],"Sentence-BERT,":[104],"stance":[105],"detection,":[106],"retrieval-augmented":[108],"generation":[109],"(RAG)":[110],"evidence-grounded":[112],"debunking.":[113],"Misinformation":[114],"instances":[115],"are":[116],"detected":[117],"through":[118],"fine-tuned":[120],"RoBERTa\u2013Multi-Genre":[121],"Inference":[124],"(MNLI)":[125],"classifier":[126],"(RoBERTa-MNLI),":[127],"grouped":[128],"BERTopic,":[130],"verified":[132],"against":[133],"curated":[134],"climate-science":[135],"knowledge":[136],"sources":[137],"BM25":[139],"dense":[141],"retrieval":[142],"via":[143],"FAISS":[144],"(Facebook":[145],"Similarity":[147],"Search).":[148],"debunking":[150,235,275],"component":[151],"RAG-enhanced":[153],"GPT-4":[154],"produce":[156],"accurate":[157],"persuasive":[159,243],"counter-messages":[160],"aligned":[161],"with":[162],"authoritative":[163],"reports":[165],"those":[168],"from":[169],"Intergovernmental":[171],"Panel":[172],"on":[173],"Climate":[174],"Change":[175],"(IPCC).":[176],"A":[177],"diverse":[178],"dataset":[179],"categories":[183],"covering":[184],"denialism,":[185],"cherry-picking":[186],"data,":[188],"false":[189],"causation":[190],"narratives,":[191],"comparisons":[194],"is":[195],"compiled":[196],"evaluation.":[198],"Benchmarking":[199],"experiments":[200],"demonstrate":[201],"LLM-based":[203],"substantially":[205],"outperform":[206],"traditional":[207],"machine-learning":[208],"baselines":[209],"Support":[212],"Vector":[213],"Machines,":[214],"Logistic":[215],"Regression,":[216],"Random":[218],"Forests":[219],"precision,":[221],"contextual":[222],"understanding,":[223],"robustness":[225],"linguistic":[227],"variation.":[228],"Expert":[229],"assessment":[230],"further":[231],"shows":[232],"generated":[234],"messages":[236],"exhibit":[237],"higher":[238],"clarity,":[239],"accuracy,":[241],"effectiveness":[244],"compared":[245],"conventional":[247],"fact-checking":[248],"text.":[249],"These":[250],"results":[251],"highlight":[252],"potential":[254],"advanced":[256],"LLM-driven":[257],"pipelines":[258],"provide":[260],"scalable,":[261],"real-time":[262],"mitigation":[263],"while":[267],"offering":[268],"guidelines":[269],"responsible":[271],"deployment":[272],"AI-assisted":[274],"systems.":[276]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2026-01-20T00:00:00"}
