{"id":"https://openalex.org/W2920675078","doi":"https://doi.org/10.1109/tencon.2018.8650350","title":"FaNDeR: Fake News Detection Model Using Media Reliability","display_name":"FaNDeR: Fake News Detection Model Using Media Reliability","publication_year":2018,"publication_date":"2018-10-01","ids":{"openalex":"https://openalex.org/W2920675078","doi":"https://doi.org/10.1109/tencon.2018.8650350","mag":"2920675078"},"language":"en","primary_location":{"id":"doi:10.1109/tencon.2018.8650350","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon.2018.8650350","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TENCON 2018 - 2018 IEEE Region 10 Conference","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/A5049262418","display_name":"Youngkyung Seo","orcid":null},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Youngkyung Seo","raw_affiliation_strings":["Department of Electrical Engineering, Korea University, Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Korea University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I197347611"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082621198","display_name":"Deokjin Seo","orcid":"https://orcid.org/0000-0002-3760-9616"},"institutions":[{"id":"https://openalex.org/I3129921980","display_name":"Korea National University of Arts","ror":"https://ror.org/0168zcn11","country_code":"KR","type":"education","lineage":["https://openalex.org/I3129921980"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Deokjin Seo","raw_affiliation_strings":["Nuua, Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Nuua, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I3129921980"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039944209","display_name":"Chang\u2010Sung Jeong","orcid":"https://orcid.org/0000-0001-9654-8406"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Chang-Sung Jeong","raw_affiliation_strings":["Department of Electrical Engineering, Korea University, Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Korea University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I197347611"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5049262418"],"corresponding_institution_ids":["https://openalex.org/I197347611"],"apc_list":null,"apc_paid":null,"fwci":5.7025,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.95899845,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1834","last_page":"1838"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11147","display_name":"Misinformation and Its Impacts","score":0.9993000030517578,"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":0.9993000030517578,"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":0.9954000115394592,"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9937999844551086,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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","display_name":"Fake news","score":0.8167394399642944},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7909715175628662},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.7648859620094299},{"id":"https://openalex.org/keywords/newspaper","display_name":"Newspaper","score":0.7022557258605957},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5585941076278687},{"id":"https://openalex.org/keywords/proposition","display_name":"Proposition","score":0.4885772168636322},{"id":"https://openalex.org/keywords/news-media","display_name":"News media","score":0.4695865511894226},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4644365906715393},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4240996241569519},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.42261844873428345},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3628596365451813},{"id":"https://openalex.org/keywords/advertising","display_name":"Advertising","score":0.1298852562904358}],"concepts":[{"id":"https://openalex.org/C2779756789","wikidata":"https://www.wikidata.org/wiki/Q28549308","display_name":"Fake news","level":2,"score":0.8167394399642944},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7909715175628662},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.7648859620094299},{"id":"https://openalex.org/C201280247","wikidata":"https://www.wikidata.org/wiki/Q11032","display_name":"Newspaper","level":2,"score":0.7022557258605957},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5585941076278687},{"id":"https://openalex.org/C2777152325","wikidata":"https://www.wikidata.org/wiki/Q108163","display_name":"Proposition","level":2,"score":0.4885772168636322},{"id":"https://openalex.org/C529147693","wikidata":"https://www.wikidata.org/wiki/Q1193236","display_name":"News media","level":2,"score":0.4695865511894226},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4644365906715393},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4240996241569519},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.42261844873428345},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3628596365451813},{"id":"https://openalex.org/C112698675","wikidata":"https://www.wikidata.org/wiki/Q37038","display_name":"Advertising","level":1,"score":0.1298852562904358},{"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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"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/C108827166","wikidata":"https://www.wikidata.org/wiki/Q175975","display_name":"Internet privacy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tencon.2018.8650350","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon.2018.8650350","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TENCON 2018 - 2018 IEEE Region 10 Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.6499999761581421}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W580074167","https://openalex.org/W1525961042","https://openalex.org/W1813062533","https://openalex.org/W1999678553","https://openalex.org/W2061141062","https://openalex.org/W2119739007","https://openalex.org/W2151149636","https://openalex.org/W2163605009","https://openalex.org/W2251202616","https://openalex.org/W2293453011","https://openalex.org/W2516930406","https://openalex.org/W2528820915","https://openalex.org/W2551396370","https://openalex.org/W2898296565","https://openalex.org/W2951008357","https://openalex.org/W2963341924","https://openalex.org/W2963579811","https://openalex.org/W2963656735","https://openalex.org/W6617055948","https://openalex.org/W6631399359","https://openalex.org/W6638318767","https://openalex.org/W6684191040","https://openalex.org/W6697449767","https://openalex.org/W6717697761","https://openalex.org/W6726253136","https://openalex.org/W6729654139","https://openalex.org/W6735013348","https://openalex.org/W6756148946"],"related_works":["https://openalex.org/W2897010431","https://openalex.org/W2610867798","https://openalex.org/W3206179000","https://openalex.org/W3102522885","https://openalex.org/W2957600470","https://openalex.org/W2604556392","https://openalex.org/W2609845429","https://openalex.org/W3007807544","https://openalex.org/W2752459574","https://openalex.org/W2899516544"],"abstract_inverted_index":{"With":[0],"the":[1,20,49,54,57,71,79,84,94,131,140,143],"development":[2],"of":[3,51,73,86,93,108,133,142],"media":[4,43,88,104,138],"including":[5],"newspaper":[6],"written":[7],"by":[8,76,129],"robots":[9],"and":[10,114],"many":[11],"unreliable":[12],"sources,":[13],"it\u2019s":[14],"getting":[15],"hard":[16],"to":[17],"distinguish":[18],"whether":[19],"news":[21,35,55],"is":[22,98],"true":[23],"or":[24],"not.":[25],"In":[26],"this":[27],"paper,":[28],"we":[29],"shall":[30,118],"present":[31],"a":[32],"novel":[33],"fake":[34],"detection":[36],"model,":[37],"FaNDeR(Fake":[38],"News":[39],"Detection":[40],"model":[41,69,97,115,122],"using":[42],"Reliability)":[44],"which":[45,82],"can":[46],"efficiently":[47],"classify":[48],"level":[50,135],"truth":[52,134],"for":[53,100,136],"in":[56,106],"question":[58],"answering":[59],"system":[60],"based":[61],"on":[62],"modified":[63],"CNN":[64],"deep":[65],"learning":[66],"model.":[67],"Our":[68,96],"reflects":[70],"reliability":[72],"various":[74],"medias":[75],"training":[77,141],"with":[78,103],"input":[80],"dataset":[81,105,144],"contains":[83],"truthfulness":[85],"each":[87,137],"as":[89,91],"well":[90],"that":[92,120],"proposition.":[95],"designed":[99],"higher":[101,124],"accuracy":[102,125],"terms":[107],"data":[109],"augmentation,":[110],"batch":[111],"size":[112],"control":[113],"modification.":[116],"We":[117],"show":[119],"our":[121],"has":[123],"over":[126],"statistical":[127],"approach":[128],"reflecting":[130],"tendency":[132],"through":[139],"collected":[145],"so":[146],"far.":[147]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
