{"id":"https://openalex.org/W4406460568","doi":"https://doi.org/10.1109/bigdata62323.2024.10825432","title":"Detecting Fake News Spreaders on Social Media Using Posts Content Versus Profile Information","display_name":"Detecting Fake News Spreaders on Social Media Using Posts Content Versus Profile Information","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4406460568","doi":"https://doi.org/10.1109/bigdata62323.2024.10825432"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata62323.2024.10825432","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825432","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","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/A5023333475","display_name":"Ifeoma Adaji","orcid":"https://orcid.org/0000-0003-2976-3039"},"institutions":[{"id":"https://openalex.org/I822440","display_name":"Okanagan University College","ror":"https://ror.org/02mxmh518","country_code":"CA","type":"education","lineage":["https://openalex.org/I822440"]},{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Ifeoma Adaji","raw_affiliation_strings":["The University of British Columbia, Okanagan,Canada"],"affiliations":[{"raw_affiliation_string":"The University of British Columbia, Okanagan,Canada","institution_ids":["https://openalex.org/I822440","https://openalex.org/I141945490"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5115905016","display_name":"Linda O. Okpanachi","orcid":"https://orcid.org/0000-0001-5795-927X"},"institutions":[{"id":"https://openalex.org/I822440","display_name":"Okanagan University College","ror":"https://ror.org/02mxmh518","country_code":"CA","type":"education","lineage":["https://openalex.org/I822440"]},{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Linda O. Okpanachi","raw_affiliation_strings":["The University of British Columbia, Okanagan,Canada"],"affiliations":[{"raw_affiliation_string":"The University of British Columbia, Okanagan,Canada","institution_ids":["https://openalex.org/I822440","https://openalex.org/I141945490"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5023333475"],"corresponding_institution_ids":["https://openalex.org/I141945490","https://openalex.org/I822440"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.41368405,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"6190","last_page":"6198"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11644","display_name":"Spam and Phishing Detection","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T11644","display_name":"Spam and Phishing Detection","score":0.9997000098228455,"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/T11147","display_name":"Misinformation and Its Impacts","score":0.9995999932289124,"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/T12262","display_name":"Hate Speech and Cyberbullying Detection","score":0.9879999756813049,"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/social-media","display_name":"Social media","score":0.7700357437133789},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6622461080551147},{"id":"https://openalex.org/keywords/content","display_name":"Content (measure theory)","score":0.5974102020263672},{"id":"https://openalex.org/keywords/fake-news","display_name":"Fake news","score":0.47260576486587524},{"id":"https://openalex.org/keywords/microblogging","display_name":"Microblogging","score":0.4640312194824219},{"id":"https://openalex.org/keywords/media-content","display_name":"Media content","score":0.46185314655303955},{"id":"https://openalex.org/keywords/internet-privacy","display_name":"Internet privacy","score":0.38527417182922363},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.34832319617271423},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.31605687737464905},{"id":"https://openalex.org/keywords/multimedia","display_name":"Multimedia","score":0.23115241527557373},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.06888771057128906}],"concepts":[{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.7700357437133789},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6622461080551147},{"id":"https://openalex.org/C2778152352","wikidata":"https://www.wikidata.org/wiki/Q5165061","display_name":"Content (measure theory)","level":2,"score":0.5974102020263672},{"id":"https://openalex.org/C2779756789","wikidata":"https://www.wikidata.org/wiki/Q28549308","display_name":"Fake news","level":2,"score":0.47260576486587524},{"id":"https://openalex.org/C143275388","wikidata":"https://www.wikidata.org/wiki/Q92438","display_name":"Microblogging","level":3,"score":0.4640312194824219},{"id":"https://openalex.org/C3020234875","wikidata":"https://www.wikidata.org/wiki/Q1260632","display_name":"Media content","level":2,"score":0.46185314655303955},{"id":"https://openalex.org/C108827166","wikidata":"https://www.wikidata.org/wiki/Q175975","display_name":"Internet privacy","level":1,"score":0.38527417182922363},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.34832319617271423},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.31605687737464905},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.23115241527557373},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.06888771057128906},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata62323.2024.10825432","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825432","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1517046895","https://openalex.org/W1522301498","https://openalex.org/W2251214593","https://openalex.org/W2591987426","https://openalex.org/W2593408211","https://openalex.org/W2763572884","https://openalex.org/W2800423036","https://openalex.org/W2914307417","https://openalex.org/W2914767245","https://openalex.org/W2924988155","https://openalex.org/W2944575651","https://openalex.org/W2998651009","https://openalex.org/W2999606367","https://openalex.org/W3007075806","https://openalex.org/W3011731543","https://openalex.org/W3012197737","https://openalex.org/W3044853528","https://openalex.org/W3045987077","https://openalex.org/W3089563032","https://openalex.org/W3092248103","https://openalex.org/W4210299703","https://openalex.org/W4281263927","https://openalex.org/W4288079542","https://openalex.org/W4308387786","https://openalex.org/W4384666235","https://openalex.org/W4385626758","https://openalex.org/W4387682197","https://openalex.org/W4389438179","https://openalex.org/W4389454219","https://openalex.org/W4392158734","https://openalex.org/W4392741075","https://openalex.org/W4392978142","https://openalex.org/W4399978342","https://openalex.org/W4400762160","https://openalex.org/W6631190155","https://openalex.org/W6636510571","https://openalex.org/W6672681305","https://openalex.org/W6783510634","https://openalex.org/W6849395510"],"related_works":["https://openalex.org/W2728430307","https://openalex.org/W2107786128","https://openalex.org/W2053241453","https://openalex.org/W2153980712","https://openalex.org/W2537388533","https://openalex.org/W2036556872","https://openalex.org/W2017590198","https://openalex.org/W2978974359","https://openalex.org/W2021183651","https://openalex.org/W2353191283"],"abstract_inverted_index":{"The":[0,122],"rapid":[1],"spread":[2],"of":[3,39,59,90,97,106,135,147,176],"misinformation":[4],"on":[5,80,100],"social":[6],"media":[7],"platforms":[8],"poses":[9],"significant":[10],"societal":[11],"challenges,":[12],"underscoring":[13],"the":[14,36,57,73,81,87,95,104,145,172],"need":[15],"for":[16,33],"effective":[17,131],"methods":[18],"to":[19],"detect":[20],"fake":[21,68,142],"news":[22,69],"spreaders.":[23,70],"While":[24],"many":[25],"studies":[26],"combine":[27],"textual":[28,60,126],"and":[29,62,93,113,141,169],"user":[30,63,148,162],"profile":[31,64,149,163],"features":[32],"this":[34,84,177],"task,":[35],"individual":[37,88],"impact":[38],"these":[40],"attributes":[41],"remains":[42],"unclear,":[43],"raising":[44],"questions":[45],"about":[46],"how":[47],"each":[48,91],"feature":[49,92,178],"independently":[50],"influences":[51],"model":[52,79,101,156],"performance.":[53,157],"This":[54],"study":[55,85],"evaluates":[56],"effectiveness":[58],"data":[61,127,150,164],"information":[65],"in":[66,116,137],"detecting":[67],"By":[71],"utilizing":[72],"Bidirectional":[74],"Long":[75],"Short-Term":[76],"Memory":[77],"(BiLSTM)":[78],"TruthSeeker":[82],"dataset,":[83],"assesses":[86],"contribution":[89],"analyzes":[94],"effect":[96],"combining":[98],"them":[99],"accuracy.":[102],"Additionally,":[103],"role":[105],"optimization":[107],"techniques,":[108],"such":[109],"as":[110],"L2":[111],"regularization":[112],"early":[114],"stopping,":[115],"improving":[117],"detection":[118],"performance":[119],"was":[120],"investigated.":[121],"results":[123],"indicate":[124],"that":[125],"alone":[128],"is":[129],"highly":[130],"(achieving":[132],"an":[133],"accuracy":[134,166],"97.78%)":[136],"distinguishing":[138],"between":[139,167],"real":[140],"news,":[143],"while":[144],"inclusion":[146],"(97.61%)":[151],"does":[152],"not":[153],"significantly":[154],"enhance":[155],"Furthermore,":[158],"models":[159],"using":[160],"only":[161],"exhibited":[165],"55%":[168],"64%,":[170],"highlighting":[171],"limited":[173],"predictive":[174],"power":[175],"set":[179],"alone.":[180]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
