{"id":"https://openalex.org/W4413442743","doi":"https://doi.org/10.1109/coins65080.2025.11125723","title":"An Adaptive and Unsupervised Graph-based Approach for Fake News Detection","display_name":"An Adaptive and Unsupervised Graph-based Approach for Fake News Detection","publication_year":2025,"publication_date":"2025-08-04","ids":{"openalex":"https://openalex.org/W4413442743","doi":"https://doi.org/10.1109/coins65080.2025.11125723"},"language":"en","primary_location":{"id":"doi:10.1109/coins65080.2025.11125723","is_oa":false,"landing_page_url":"https://doi.org/10.1109/coins65080.2025.11125723","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Omni-layer Intelligent Systems (COINS)","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/A5119394220","display_name":"Manish Vikrama","orcid":null},"institutions":[{"id":"https://openalex.org/I157638225","display_name":"California State University, Northridge","ror":"https://ror.org/005f5hv41","country_code":"US","type":"education","lineage":["https://openalex.org/I157638225"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Manish Vikrama","raw_affiliation_strings":["California State University,Department of Computer Science,Northridge,California,USA"],"affiliations":[{"raw_affiliation_string":"California State University,Department of Computer Science,Northridge,California,USA","institution_ids":["https://openalex.org/I157638225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119394221","display_name":"Monitha Davuluri","orcid":null},"institutions":[{"id":"https://openalex.org/I157638225","display_name":"California State University, Northridge","ror":"https://ror.org/005f5hv41","country_code":"US","type":"education","lineage":["https://openalex.org/I157638225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Monitha Davuluri","raw_affiliation_strings":["California State University,Department of Computer Science,Northridge,California,USA"],"affiliations":[{"raw_affiliation_string":"California State University,Department of Computer Science,Northridge,California,USA","institution_ids":["https://openalex.org/I157638225"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091820414","display_name":"Rashida Hasan","orcid":"https://orcid.org/0000-0002-6231-8116"},"institutions":[{"id":"https://openalex.org/I157638225","display_name":"California State University, Northridge","ror":"https://ror.org/005f5hv41","country_code":"US","type":"education","lineage":["https://openalex.org/I157638225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rashida Hasan","raw_affiliation_strings":["California State University,Department of Computer Science,Northridge,California,USA"],"affiliations":[{"raw_affiliation_string":"California State University,Department of Computer Science,Northridge,California,USA","institution_ids":["https://openalex.org/I157638225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5119394220"],"corresponding_institution_ids":["https://openalex.org/I157638225"],"apc_list":null,"apc_paid":null,"fwci":4.3825,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.94593315,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11147","display_name":"Misinformation and Its Impacts","score":1.0,"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":1.0,"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":0.9980999827384949,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9769999980926514,"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/computer-science","display_name":"Computer science","score":0.7152667045593262},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.45717909932136536},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39330923557281494},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.16735827922821045}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7152667045593262},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.45717909932136536},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39330923557281494},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.16735827922821045}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/coins65080.2025.11125723","is_oa":false,"landing_page_url":"https://doi.org/10.1109/coins65080.2025.11125723","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Omni-layer Intelligent Systems (COINS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1832693441","https://openalex.org/W2086413055","https://openalex.org/W2155160033","https://openalex.org/W2169585110","https://openalex.org/W2604264634","https://openalex.org/W2903981179","https://openalex.org/W2962946486","https://openalex.org/W2963416784","https://openalex.org/W2970398671","https://openalex.org/W2997128522","https://openalex.org/W3004200020","https://openalex.org/W3031781733","https://openalex.org/W3032990727","https://openalex.org/W3036963250","https://openalex.org/W3130666089","https://openalex.org/W3153567752","https://openalex.org/W3174306305","https://openalex.org/W4321485409","https://openalex.org/W4322614756","https://openalex.org/W4367046795","https://openalex.org/W4391687483","https://openalex.org/W4392507474","https://openalex.org/W4393158655","https://openalex.org/W4396594864"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Detecting":[0],"fake":[1,25,91,174],"news":[2,26,35,56,92,175],"has":[3],"become":[4],"a":[5,44,77,125],"significant":[6],"challenge":[7],"in":[8,177],"the":[9,29,34,52,80,148,154],"digital":[10],"era":[11],"today,":[12],"where":[13],"false":[14],"information":[15,179],"spreads":[16,36],"rapidly":[17],"across":[18],"various":[19],"platforms.":[20],"Current":[21],"methods":[22],"for":[23,89,133,173],"detecting":[24],"often":[27,47],"overlook":[28],"social":[30],"context":[31],"of":[32,79,156],"how":[33],"and":[37,59,72,102,114,119,140,146,167],"rely":[38],"primarily":[39],"on":[40],"labeled":[41],"datasets.":[42],"As":[43],"result,":[45],"they":[46],"struggle":[48],"to":[49,64,84,143,160],"effectively":[50],"capture":[51],"nuanced":[53],"relationships":[54,98],"between":[55],"topics,":[57],"entities,":[58,101],"content.":[60],"This":[61],"paper":[62],"aims":[63],"address":[65],"these":[66],"challenges":[67],"by":[68],"proposing":[69],"an":[70],"unsupervised":[71],"adaptive":[73,105,137],"framework":[74],"that":[75],"utilizes":[76],"variant":[78],"Graph":[81],"Sage":[82],"Autoencoder":[83],"process":[85],"heterogeneous":[86],"graph":[87,149],"data":[88,106],"improved":[90,164],"detection.":[93],"Our":[94],"approach":[95,158],"captures":[96],"complex":[97,178],"among":[99],"articles,":[100],"topics":[103],"using":[104],"augmentation":[107],"techniques":[108],"such":[109],"as":[110],"node":[111,134],"feature":[112,138],"masking":[113,139],"edge":[115,141],"dropping,":[116],"enhancing":[117],"robustness":[118,168],"generalization.":[120],"Using":[121],"SAGEConv":[122],"layers":[123],"within":[124],"contrastive":[126],"learning":[127],"framework,":[128],"it":[129],"produces":[130],"informative":[131],"embeddings":[132],"classification,":[135],"incorporating":[136],"dropping":[142],"selectively":[144],"balance":[145],"refine":[147],"structure.":[150],"Experimental":[151],"results":[152],"highlight":[153],"superiority":[155],"our":[157],"compared":[159],"state-of-the-art":[161],"algorithms,":[162],"demonstrating":[163],"detection":[165,176],"accuracy":[166],"while":[169],"ensuring":[170],"high":[171],"scalability":[172],"networks.":[180]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-02-27T16:54:17.756197","created_date":"2025-10-10T00:00:00"}