{"id":"https://openalex.org/W4417456749","doi":"https://doi.org/10.1145/3748522.3779831","title":"Integrating Causal Reasoning into Automated Fact-Checking","display_name":"Integrating Causal Reasoning into Automated Fact-Checking","publication_year":2026,"publication_date":"2026-03-23","ids":{"openalex":"https://openalex.org/W4417456749","doi":"https://doi.org/10.1145/3748522.3779831"},"language":"en","primary_location":{"id":"doi:10.1145/3748522.3779831","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3748522.3779831","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 41st ACM/SIGAPP Symposium on Applied Computing","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3748522.3779831","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5082724158","display_name":"Youssra Rebboud","orcid":"https://orcid.org/0000-0003-3507-5646"},"institutions":[{"id":"https://openalex.org/I1902872","display_name":"EURECOM","ror":"https://ror.org/00sse7z02","country_code":"FR","type":"education","lineage":["https://openalex.org/I1902872","https://openalex.org/I205703379"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Youssra Rebboud","raw_affiliation_strings":["Data Science, EURECOM, Sophia Antipolis, France"],"raw_orcid":"https://orcid.org/0000-0003-3507-5646","affiliations":[{"raw_affiliation_string":"Data Science, EURECOM, Sophia Antipolis, France","institution_ids":["https://openalex.org/I1902872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004094196","display_name":"Pasquale Lisena","orcid":"https://orcid.org/0000-0003-3094-5585"},"institutions":[{"id":"https://openalex.org/I1902872","display_name":"EURECOM","ror":"https://ror.org/00sse7z02","country_code":"FR","type":"education","lineage":["https://openalex.org/I1902872","https://openalex.org/I205703379"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Pasquale Lisena","raw_affiliation_strings":["Data Science, EURECOM, Sophia Antipolis, France"],"raw_orcid":"https://orcid.org/0000-0003-3094-5585","affiliations":[{"raw_affiliation_string":"Data Science, EURECOM, Sophia Antipolis, France","institution_ids":["https://openalex.org/I1902872"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022574838","display_name":"Rapha\u00ebl Troncy","orcid":"https://orcid.org/0000-0003-0457-1436"},"institutions":[{"id":"https://openalex.org/I1902872","display_name":"EURECOM","ror":"https://ror.org/00sse7z02","country_code":"FR","type":"education","lineage":["https://openalex.org/I1902872","https://openalex.org/I205703379"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Rapha\u00ebl Troncy","raw_affiliation_strings":["Data Science, EURECOM, Sophia Antipolis, France"],"raw_orcid":"https://orcid.org/0000-0003-0457-1436","affiliations":[{"raw_affiliation_string":"Data Science, EURECOM, Sophia Antipolis, France","institution_ids":["https://openalex.org/I1902872"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.01517677,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"947","last_page":"949"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.44999998807907104,"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"}},"topics":[{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.44999998807907104,"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/T10028","display_name":"Topic Modeling","score":0.1712000072002411,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.09939999878406525,"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/event","display_name":"Event (particle physics)","score":0.605400025844574},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.5394999980926514},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.42149999737739563},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.4113999903202057},{"id":"https://openalex.org/keywords/causal-reasoning","display_name":"Causal reasoning","score":0.3734999895095825},{"id":"https://openalex.org/keywords/case-based-reasoning","display_name":"Case-based reasoning","score":0.34950000047683716},{"id":"https://openalex.org/keywords/logical-conjunction","display_name":"Logical conjunction","score":0.34769999980926514},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.3100000023841858}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6988999843597412},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.605400025844574},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6040999889373779},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.5394999980926514},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.42149999737739563},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.4113999903202057},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3889000117778778},{"id":"https://openalex.org/C115086926","wikidata":"https://www.wikidata.org/wiki/Q17004651","display_name":"Causal reasoning","level":3,"score":0.3734999895095825},{"id":"https://openalex.org/C20162079","wikidata":"https://www.wikidata.org/wiki/Q1151406","display_name":"Case-based reasoning","level":2,"score":0.34950000047683716},{"id":"https://openalex.org/C21847791","wikidata":"https://www.wikidata.org/wiki/Q191081","display_name":"Logical conjunction","level":2,"score":0.34769999980926514},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3402000069618225},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.335099995136261},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3100000023841858},{"id":"https://openalex.org/C134752490","wikidata":"https://www.wikidata.org/wiki/Q374182","display_name":"Logical consequence","level":2,"score":0.3077999949455261},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.30079999566078186},{"id":"https://openalex.org/C79897977","wikidata":"https://www.wikidata.org/wiki/Q5054568","display_name":"Causal chain","level":2,"score":0.2897000014781952},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2874000072479248},{"id":"https://openalex.org/C195344581","wikidata":"https://www.wikidata.org/wiki/Q2555318","display_name":"Automated reasoning","level":2,"score":0.2867000102996826},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.2797999978065491},{"id":"https://openalex.org/C64357122","wikidata":"https://www.wikidata.org/wiki/Q1149766","display_name":"Causality (physics)","level":2,"score":0.27399998903274536},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.26840001344680786},{"id":"https://openalex.org/C156201811","wikidata":"https://www.wikidata.org/wiki/Q5418360","display_name":"Evidential reasoning approach","level":4,"score":0.2603999972343445}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3748522.3779831","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3748522.3779831","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 41st ACM/SIGAPP Symposium on Applied Computing","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2512.13286","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.13286","pdf_url":"https://arxiv.org/pdf/2512.13286","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"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","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:HAL:hal-05507383v1","is_oa":true,"landing_page_url":"https://hal.science/hal-05507383","pdf_url":"https://hal.science/hal-05507383v1/document","source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"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":"KNLP 2026, 41st ACM SAC Symposium on Applied Computing, Special Track on Knowledge and Natural Language Processing, ACM, Mar 2026, Thessaloniki, Greece. ⟨10.1145/3748522.3779831⟩","raw_type":"Conference papers"}],"best_oa_location":{"id":"doi:10.1145/3748522.3779831","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3748522.3779831","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 41st ACM/SIGAPP Symposium on Applied Computing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2251298042","display_name":"Climate Misinformation Surveillance with Multidimensional GIS","funder_award_id":"EP/Z003504/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G253081027","display_name":null,"funder_award_id":"ANR-24-CHR4-0002","funder_id":"https://openalex.org/F4320338463","funder_display_name":"CHIST-ERA"},{"id":"https://openalex.org/G2919578093","display_name":null,"funder_award_id":"ANR-21-CE23-0028","funder_id":"https://openalex.org/F4320320883","funder_display_name":"Agence Nationale de la Recherche"},{"id":"https://openalex.org/G4317239047","display_name":"Climate Misinformation Surveillance and Analysis with Multidimensional GIS","funder_award_id":"ANR-24-CHR4-0002","funder_id":"https://openalex.org/F4320320883","funder_display_name":"Agence Nationale de la Recherche"}],"funders":[{"id":"https://openalex.org/F4320320883","display_name":"Agence Nationale de la Recherche","ror":"https://ror.org/00rbzpz17"},{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"},{"id":"https://openalex.org/F4320338463","display_name":"CHIST-ERA","ror":"https://ror.org/00rbzpz17"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"fact-checking":[1,27,80,95],"applications,":[2],"a":[3,8,35,48,71],"common":[4],"reason":[5],"to":[6,11,61],"reject":[7],"claim":[9,72],"is":[10],"detect":[12,62],"the":[13,20,85],"presence":[14],"of":[15,67,99],"erroneous":[16],"cause-effect":[17],"relationships":[18,93],"between":[19,65],"events":[21,68],"at":[22],"play.":[23],"However,":[24],"current":[25],"automated":[26],"methods":[28],"lack":[29],"dedicated":[30],"causal-based":[31],"reasoning,":[32],"potentially":[33],"missing":[34],"valuable":[36],"opportunity":[37],"for":[38,88],"semantically":[39],"rich":[40],"explainability.":[41],"To":[42],"address":[43],"this":[44,82],"gap,":[45],"we":[46],"propose":[47],"methodology":[49],"that":[50],"combines":[51],"event":[52,92],"relation":[53],"extraction,":[54],"semantic":[55],"similarity":[56],"computation,":[57],"and":[58,73,96],"rule-based":[59],"reasoning":[60],"logical":[63],"inconsistencies":[64],"chains":[66],"mentioned":[69],"in":[70,74],"an":[75],"evidence.":[76],"Evaluated":[77],"on":[78],"two":[79],"datasets,":[81],"method":[83],"establishes":[84],"first":[86],"baseline":[87],"integrating":[89],"fine-grained":[90],"causal":[91],"into":[94],"enhance":[97],"explainability":[98],"verdict":[100],"prediction.":[101]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-12-17T00:00:00"}