{"id":"https://openalex.org/W7166324155","doi":"https://doi.org/10.1007/s44163-026-01669-3","title":"Behavior-centric deep learning framework for detecting fake or harmful content using user interaction patterns and side information","display_name":"Behavior-centric deep learning framework for detecting fake or harmful content using user interaction patterns and side information","publication_year":2026,"publication_date":"2026-06-28","ids":{"openalex":"https://openalex.org/W7166324155","doi":"https://doi.org/10.1007/s44163-026-01669-3"},"language":"en","primary_location":{"id":"doi:10.1007/s44163-026-01669-3","doi":"https://doi.org/10.1007/s44163-026-01669-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-026-01669-3","pdf_url":null,"source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","jufo-1","norway-1"],"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1007/s44163-026-01669-3","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076118304","display_name":"V. S. Nivedita","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210133257","display_name":"KPR Institute of Engineering and Technology","ror":"https://ror.org/02q9f3a53","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210133257"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"V. S. Nivedita","raw_affiliation_strings":["Department of Computer Science and Business Systems, KPR Institute of Engineering and Technology, Coimbatore, 641407, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Business Systems, KPR Institute of Engineering and Technology, Coimbatore, 641407, India","institution_ids":["https://openalex.org/I4210133257"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066219929","display_name":"A. Bazila Banu","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210133257","display_name":"KPR Institute of Engineering and Technology","ror":"https://ror.org/02q9f3a53","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210133257"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"A. Bazila Banu","raw_affiliation_strings":["Department of Computer Science and Business Systems, KPR Institute of Engineering and Technology, Coimbatore, 641407, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Business Systems, KPR Institute of Engineering and Technology, Coimbatore, 641407, India","institution_ids":["https://openalex.org/I4210133257"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5076118304"],"corresponding_institution_ids":["https://openalex.org/I4210133257"],"apc_list":{"value":1590,"currency":"USD","value_usd":1590},"apc_paid":{"value":1590,"currency":"USD","value_usd":1590},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.50808019,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"6","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11147","display_name":"Misinformation and Its Impacts","score":0.9937000274658203,"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":0.9937000274658203,"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":0.004600000102072954,"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/T12262","display_name":"Hate Speech and Cyberbullying Detection","score":0.0008999999845400453,"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/harmful-content-detection","display_name":"harmful content detection","score":0.8709999918937683},{"id":"https://openalex.org/keywords/fake-news-detection","display_name":"fake news detection","score":0.8669999837875366},{"id":"https://openalex.org/keywords/misinformation","display_name":"misinformation","score":0.5429999828338623},{"id":"https://openalex.org/keywords/user-interaction-patterns","display_name":"user interaction patterns","score":0.7519999742507935},{"id":"https://openalex.org/keywords/temporal-user-behavior","display_name":"temporal user behavior","score":0.6990000009536743},{"id":"https://openalex.org/keywords/user-metadata","display_name":"user metadata","score":0.6859999895095825},{"id":"https://openalex.org/keywords/attention-based-fusion","display_name":"attention fusion","score":0.414000004529953},{"id":"https://openalex.org/keywords/social-media","display_name":"social media","score":0.4959999918937683},{"id":"https://openalex.org/keywords/fakenewsnet","display_name":"FakeNewsNet","score":0.7400000095367432}],"concepts":[{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6952000260353088},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6312000155448914},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5756000280380249},{"id":"https://openalex.org/C2778152352","wikidata":"https://www.wikidata.org/wiki/Q5165061","display_name":"Content (measure theory)","level":2,"score":0.44179999828338623},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.367000013589859},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.3382999897003174},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.33230000734329224},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.33160001039505005},{"id":"https://openalex.org/C101293273","wikidata":"https://www.wikidata.org/wiki/Q579716","display_name":"User-generated content","level":3,"score":0.2888999879360199},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2727000117301941},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.2635999917984009}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s44163-026-01669-3","doi":"https://doi.org/10.1007/s44163-026-01669-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-026-01669-3","pdf_url":null,"source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","jufo-1","norway-1"],"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:d2560c9c67c34fed8ac904ee30ab832c","doi":null,"is_oa":false,"landing_page_url":"https://doaj.org/article/d2560c9c67c34fed8ac904ee30ab832c","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,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Discover Artificial Intelligence, Vol 6, Iss 1 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s44163-026-01669-3","doi":"https://doi.org/10.1007/s44163-026-01669-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-026-01669-3","pdf_url":null,"source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","jufo-1","norway-1"],"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"sustainable_development_goals_aurora":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.4018915295600891}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W2918817764","https://openalex.org/W2980986395","https://openalex.org/W4220768044","https://openalex.org/W4225908946","https://openalex.org/W4288740383","https://openalex.org/W4313201185","https://openalex.org/W4319303225","https://openalex.org/W4379801086","https://openalex.org/W4385750077","https://openalex.org/W4386420896","https://openalex.org/W4392135948","https://openalex.org/W4398256042","https://openalex.org/W4399269701","https://openalex.org/W4403524849","https://openalex.org/W4412573549"],"related_works":[],"abstract_inverted_index":{"The":[0,79,133],"rapid":[1],"spread":[2],"of":[3,164,167,170,174,181,184,190],"deceptive":[4],"and":[5,24,75,97,146,172,186,199],"harmful":[6,68,127],"content":[7,35],"on":[8,34],"social":[9],"media":[10],"has":[11],"created":[12],"a":[13,61,85,98,107,116,162],"need":[14],"for":[15,66,125],"detection":[16,31,212],"models":[17,202],"that":[18,120,157,204],"can":[19],"operate":[20],"effectively":[21],"under":[22,214],"sparse":[23],"limited":[25],"user":[26,69,95,104,144],"activity":[27,70,128],"conditions.":[28],"Many":[29],"existing":[30],"approaches":[32],"depend":[33],"features,":[36],"item-level":[37],"representations,":[38],"or":[39,48],"dense":[40,99],"interaction":[41,73,131],"histories,":[42],"which":[43,142],"may":[44],"be":[45],"unavailable,":[46],"incomplete,":[47],"unreliable":[49],"in":[50,106],"early-stage":[51],"online":[52],"environments.":[53],"To":[54],"address":[55],"this":[56,58],"limitation,":[57],"study":[59],"proposes":[60],"behavior-centric":[62,207],"deep":[63],"learning":[64],"framework":[65,160],"identifying":[67],"using":[71,138],"temporal":[72],"patterns":[74],"contextual":[76],"side":[77],"information.":[78],"proposed":[80,134,159,206],"architecture,":[81],"GRU-Metadata-Contrast-Attention-Fusion":[82],"(GRU-MCAF)":[83],"employs":[84],"Bidirectional":[86],"Gated":[87],"Recurrent":[88],"Unit":[89],"(Bi-GRU)":[90],"encoder":[91],"to":[92,102],"capture":[93],"sequential":[94],"behavior":[96],"projection":[100],"layer":[101],"represent":[103],"metadata":[105],"compatible":[108],"latent":[109],"space.":[110],"These":[111],"representations":[112],"are":[113],"integrated":[114],"through":[115],"contrast-guided":[117],"attention":[118],"mechanism":[119],"highlights":[121],"behavior\u2013metadata":[122],"deviations":[123],"useful":[124],"distinguishing":[126],"from":[129],"normal":[130],"patterns.":[132],"model":[135],"is":[136],"evaluated":[137],"the":[139,158,205,215],"FakeNewsNet":[140],"dataset,":[141],"provides":[143,210],"profiles":[145],"engagement":[147],"logs":[148],"associated":[149],"with":[150],"verified":[151],"misinformation":[152],"labels.":[153],"Experimental":[154],"results":[155],"show":[156],"achieved":[161],"precision":[163],"95.13%,":[165],"recall":[166],"94.68%,":[168],"accuracy":[169],"94.82%,":[171],"F1-score":[173],"94.90%.":[175],"It":[176],"also":[177],"obtained":[178],"an":[179],"MCC":[180],"0.901,":[182],"AUC":[183],"0.969,":[185],"false":[187],"positive":[188],"rate":[189],"4.16%.":[191],"Comparative":[192],"evaluation":[193],"against":[194],"CNN,":[195],"GRU,":[196],"Bi-LSTM,":[197],"EfficientNet-B0,":[198],"attention-based":[200],"LSTM":[201],"indicates":[203],"fusion":[208],"strategy":[209],"improved":[211],"performance":[213],"considered":[216],"experimental":[217],"setting.":[218]},"counts_by_year":[],"updated_date":"2026-09-22T17:25:34.749102","created_date":"2026-06-28T00:00:00"}
