{"id":"https://openalex.org/W4415772001","doi":"https://doi.org/10.54938/ijemdcsai.2025.04.1.545","title":"Enhancing Fake News Detection Models Through Modified Cosine Similarity (MCS) Using Sorensen-Dice Distance","display_name":"Enhancing Fake News Detection Models Through Modified Cosine Similarity (MCS) Using Sorensen-Dice Distance","publication_year":2025,"publication_date":"2025-11-02","ids":{"openalex":"https://openalex.org/W4415772001","doi":"https://doi.org/10.54938/ijemdcsai.2025.04.1.545"},"language":"en","primary_location":{"id":"doi:10.54938/ijemdcsai.2025.04.1.545","doi":"https://doi.org/10.54938/ijemdcsai.2025.04.1.545","is_oa":true,"landing_page_url":"https://doi.org/10.54938/ijemdcsai.2025.04.1.545","pdf_url":"https://ojs.ijemd.com/index.php/ComputerScienceAI/article/download/545/292","source":{"id":"https://openalex.org/S4387280677","display_name":"International Journal of Emerging Multidisciplinaries Computer Science & Artificial Intelligence","issn_l":"2791-0164","issn":["2791-0164","2957-5036"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Emerging Multidisciplinaries: Computer Science & Artificial Intelligence","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://ojs.ijemd.com/index.php/ComputerScienceAI/article/download/545/292","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5003122497","display_name":"Aliyu Rabiu Shuaibu","orcid":"https://orcid.org/0000-0002-8789-9199","observed_orcids":["https://orcid.org/0000-0002-8789-9199"]},"institutions":[{"id":"https://openalex.org/I919958821","display_name":"Bayero University Kano","ror":"https://ror.org/049pzty39","country_code":"NG","type":"education","lineage":["https://openalex.org/I919958821"]}],"countries":["NG"],"is_corresponding":true,"raw_author_name":"Aliyu Shuaibu *","raw_affiliation_strings":["Department of Computer Science, Faculty of Computing, Bayero University, Kano, Nigeria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Faculty of Computing, Bayero University, Kano, Nigeria","institution_ids":["https://openalex.org/I919958821"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045208861","display_name":"Hadiza Ali Umar","orcid":"https://orcid.org/0000-0002-6214-6537","observed_orcids":["https://orcid.org/0000-0002-6214-6537"]},"institutions":[{"id":"https://openalex.org/I919958821","display_name":"Bayero University Kano","ror":"https://ror.org/049pzty39","country_code":"NG","type":"education","lineage":["https://openalex.org/I919958821"]}],"countries":["NG"],"is_corresponding":false,"raw_author_name":"Hadiza Ali Umar","raw_affiliation_strings":["Department of Computer Science, Faculty of Computing, Bayero University, Kano, Nigeria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Faculty of Computing, Bayero University, Kano, Nigeria","institution_ids":["https://openalex.org/I919958821"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5120059821","display_name":"Yusuf Tijjani Baffa","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I919958821","display_name":"Bayero University Kano","ror":"https://ror.org/049pzty39","country_code":"NG","type":"education","lineage":["https://openalex.org/I919958821"]}],"countries":["NG"],"is_corresponding":false,"raw_author_name":"Yusuf Tijjani Baffa","raw_affiliation_strings":["Department of Software Engineering, Faculty of Computing, Bayero University, Kano, Nigeria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Software Engineering, Faculty of Computing, Bayero University, Kano, Nigeria","institution_ids":["https://openalex.org/I919958821"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5003122497"],"corresponding_institution_ids":["https://openalex.org/I919958821"],"apc_list":null,"apc_paid":null,"fwci":0.9488,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.71963537,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"4","issue":"1","first_page":"17","last_page":"17"},"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":0.00019999999494757503,"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"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":9.999999747378752e-05,"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/fake-news-detection","display_name":"fake news detection","score":1.0},{"id":"https://openalex.org/keywords/text-similarity-measures","display_name":"text similarity measures","score":0.7990000247955322},{"id":"https://openalex.org/keywords/semantic-text-representation","display_name":"semantic text representation","score":0.5669999718666077},{"id":"https://openalex.org/keywords/lstm","display_name":"LSTM","score":0.5339999794960022},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"support vector machine","score":0.8389999866485596},{"id":"https://openalex.org/keywords/random-forest","display_name":"random forest","score":0.8949999809265137},{"id":"https://openalex.org/keywords/k-nearest-neighbors","display_name":"k-nearest neighbors","score":0.925000011920929},{"id":"https://openalex.org/keywords/text-classification","display_name":"text classification","score":0.4410000145435333}],"concepts":[{"id":"https://openalex.org/C2780762811","wikidata":"https://www.wikidata.org/wiki/Q1784941","display_name":"Cosine similarity","level":3,"score":0.7760999798774719},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.7246999740600586},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.6948000192642212},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6148999929428101},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5626000165939331},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5547000169754028},{"id":"https://openalex.org/C178009071","wikidata":"https://www.wikidata.org/wiki/Q93344","display_name":"Trigonometric functions","level":2,"score":0.5418999791145325},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5157999992370605},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.49570000171661377},{"id":"https://openalex.org/C2221639","wikidata":"https://www.wikidata.org/wiki/Q2877","display_name":"Discrete cosine transform","level":3,"score":0.49050000309944153},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.450300008058548},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.41600000858306885},{"id":"https://openalex.org/C2776517306","wikidata":"https://www.wikidata.org/wiki/Q29017317","display_name":"Similarity measure","level":2,"score":0.382999986410141},{"id":"https://openalex.org/C2779086471","wikidata":"https://www.wikidata.org/wiki/Q2051704","display_name":"False memory","level":3,"score":0.3635999858379364},{"id":"https://openalex.org/C143271835","wikidata":"https://www.wikidata.org/wiki/Q254515","display_name":"Similitude","level":2,"score":0.3366999924182892},{"id":"https://openalex.org/C2639959","wikidata":"https://www.wikidata.org/wiki/Q1344778","display_name":"Distance measures","level":2,"score":0.328900009393692},{"id":"https://openalex.org/C129782007","wikidata":"https://www.wikidata.org/wiki/Q162886","display_name":"Euclidean geometry","level":2,"score":0.32850000262260437},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.3206999897956848},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.31630000472068787},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.30709999799728394},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.3012000024318695},{"id":"https://openalex.org/C95922358","wikidata":"https://www.wikidata.org/wiki/Q5432725","display_name":"False positive rate","level":2,"score":0.2896000146865845},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.2768999934196472},{"id":"https://openalex.org/C2987098735","wikidata":"https://www.wikidata.org/wiki/Q3808900","display_name":"Recall rate","level":2,"score":0.2694999873638153},{"id":"https://openalex.org/C116738811","wikidata":"https://www.wikidata.org/wiki/Q608751","display_name":"Nearest neighbor search","level":2,"score":0.25130000710487366}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.54938/ijemdcsai.2025.04.1.545","doi":"https://doi.org/10.54938/ijemdcsai.2025.04.1.545","is_oa":true,"landing_page_url":"https://doi.org/10.54938/ijemdcsai.2025.04.1.545","pdf_url":"https://ojs.ijemd.com/index.php/ComputerScienceAI/article/download/545/292","source":{"id":"https://openalex.org/S4387280677","display_name":"International Journal of Emerging Multidisciplinaries Computer Science & Artificial Intelligence","issn_l":"2791-0164","issn":["2791-0164","2957-5036"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Emerging Multidisciplinaries: Computer Science & Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.54938/ijemdcsai.2025.04.1.545","doi":"https://doi.org/10.54938/ijemdcsai.2025.04.1.545","is_oa":true,"landing_page_url":"https://doi.org/10.54938/ijemdcsai.2025.04.1.545","pdf_url":"https://ojs.ijemd.com/index.php/ComputerScienceAI/article/download/545/292","source":{"id":"https://openalex.org/S4387280677","display_name":"International Journal of Emerging Multidisciplinaries Computer Science & Artificial Intelligence","issn_l":"2791-0164","issn":["2791-0164","2957-5036"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Emerging Multidisciplinaries: Computer Science & Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4415772001.pdf","grobid_xml":"https://content.openalex.org/works/W4415772001.grobid-xml"},"referenced_works_count":8,"referenced_works":["https://openalex.org/W62038714","https://openalex.org/W3045984998","https://openalex.org/W3122910157","https://openalex.org/W3165299977","https://openalex.org/W4220939111","https://openalex.org/W4221143803","https://openalex.org/W4361004942","https://openalex.org/W7131825856"],"related_works":["https://openalex.org/W7162938691","https://openalex.org/W4413860812","https://openalex.org/W3196264289","https://openalex.org/W7202194517","https://openalex.org/W7117259495","https://openalex.org/W4408859319","https://openalex.org/W4400057188","https://openalex.org/W4412502181","https://openalex.org/W4409018893","https://openalex.org/W4401486889"],"abstract_inverted_index":{"The":[0],"rapid":[1],"spread":[2],"of":[3,144],"fake":[4,185],"news":[5,186],"undermines":[6],"public":[7],"trust":[8],"and":[9,52,69,89,97,130,136,146,155,174],"highlights":[10],"the":[11,85,111],"need":[12],"for":[13,183],"more":[14],"reliable":[15],"detection":[16],"models.":[17],"Traditional":[18],"approaches,":[19],"such":[20],"as":[21],"LSTM":[22,109],"with":[23,49,82,104,121,142],"standard":[24],"cosine":[25,77,168],"similarity":[26,78,169,181],"using":[27,76],"Euclidean":[28,47],"distance,":[29],"often":[30],"fail":[31],"to":[32],"capture":[33],"subtle":[34],"textual":[35],"relationships.":[36],"This":[37],"study":[38],"introduces":[39],"a":[40,179],"Modified":[41],"Cosine":[42],"Similarity":[43],"(MCS)":[44],"that":[45,163],"replaces":[46],"distance":[48,51,166],"S\u00f8rensen-Dice":[50,165],"evaluates":[53],"its":[54],"effectiveness":[55],"across":[56,158],"four":[57],"models:":[58],"Long":[59],"Short-Term":[60],"Memory":[61],"(LSTM),":[62],"K-Nearest":[63],"Neighbor":[64],"(KNN),":[65],"Random":[66],"Forest":[67],"(RF),":[68],"Support":[70],"Vector":[71],"Machine":[72],"(SVM).":[73],"Baseline":[74],"results":[75,113],"showed":[79,139],"strong":[80],"performance,":[81,176],"SVM":[83,135],"achieving":[84],"highest":[86],"accuracy":[87],"(0.987)":[88],"F1-score":[90,119],"(0.986),":[91],"followed":[92],"by":[93],"RF":[94,150],"(accuracy":[95,99,115],"0.979)":[96],"KNN":[98,137],"0.973).":[100],"However,":[101],"enhanced":[102],"models":[103],"MCS":[105,178],"demonstrated":[106],"substantial":[107],"improvements.":[108],"achieved":[110],"best":[112],"overall":[114],"0.997,":[116],"recall":[117,153],"0.998,":[118],"0.997)":[120],"reduced":[122],"cross-entropy":[123],"loss":[124],"(0.016),":[125],"false":[126,131],"positive":[127],"rate":[128,133],"(0.005),":[129],"negative":[132],"(0.002).":[134],"also":[138],"notable":[140],"gains":[141],"accuracies":[143],"0.995":[145],"0.991,":[147],"respectively,":[148],"while":[149],"recorded":[151],"high":[152],"(0.995)":[154],"competitive":[156],"performance":[157],"metrics.":[159],"These":[160],"findings":[161],"confirm":[162],"integrating":[164],"into":[167],"significantly":[170],"boosts":[171],"semantic":[172],"representation":[173],"model":[175],"making":[177],"robust":[180],"measure":[182],"advancing":[184],"detection.":[187]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2025-11-02T00:00:00"}