{"id":"https://openalex.org/W4225586908","doi":"https://doi.org/10.1145/3486622.3493939","title":"Fake News Detection via Biased User Profiles in Social Networking Sites","display_name":"Fake News Detection via Biased User Profiles in Social Networking Sites","publication_year":2021,"publication_date":"2021-12-14","ids":{"openalex":"https://openalex.org/W4225586908","doi":"https://doi.org/10.1145/3486622.3493939"},"language":"en","primary_location":{"id":"doi:10.1145/3486622.3493939","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3486622.3493939","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3486622.3493939","source":{"id":"https://openalex.org/S4363608074","display_name":"IEEE/WIC/ACM International Conference on Web Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/WIC/ACM International Conference on Web Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3486622.3493939","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5090831474","display_name":"Ryoya Furukawa","orcid":"https://orcid.org/0000-0003-2517-8561"},"institutions":[{"id":"https://openalex.org/I65837984","display_name":"Kobe University","ror":"https://ror.org/03tgsfw79","country_code":"JP","type":"education","lineage":["https://openalex.org/I65837984"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Ryoya Furukawa","raw_affiliation_strings":["Deloitte Tohmatsu Cyber LLC, Japan and Kobe University, Japan"],"affiliations":[{"raw_affiliation_string":"Deloitte Tohmatsu Cyber LLC, Japan and Kobe University, Japan","institution_ids":["https://openalex.org/I65837984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103284951","display_name":"Daiki Ito","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Daiki Ito","raw_affiliation_strings":["Deloitte Tohmatsu Cyber LLC, Japan"],"affiliations":[{"raw_affiliation_string":"Deloitte Tohmatsu Cyber LLC, Japan","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024697484","display_name":"Yuta Takata","orcid":"https://orcid.org/0009-0008-2773-0659"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuta Takata","raw_affiliation_strings":["Deloitte Tohmatsu Cyber LLC, Japan"],"affiliations":[{"raw_affiliation_string":"Deloitte Tohmatsu Cyber LLC, Japan","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107920377","display_name":"Hiroshi Kumagai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hiroshi Kumagai","raw_affiliation_strings":["Deloitte Tohmatsu Cyber LLC, Japan"],"affiliations":[{"raw_affiliation_string":"Deloitte Tohmatsu Cyber LLC, Japan","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084427817","display_name":"Masaki Kamizono","orcid":"https://orcid.org/0009-0007-9467-2412"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Masaki Kamizono","raw_affiliation_strings":["Deloitte Tohmatsu Cyber LLC, Japan"],"affiliations":[{"raw_affiliation_string":"Deloitte Tohmatsu Cyber LLC, Japan","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076797774","display_name":"Yoshiaki Shiraishi","orcid":"https://orcid.org/0000-0002-8970-9408"},"institutions":[{"id":"https://openalex.org/I65837984","display_name":"Kobe University","ror":"https://ror.org/03tgsfw79","country_code":"JP","type":"education","lineage":["https://openalex.org/I65837984"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yoshiaki Shiraishi","raw_affiliation_strings":["Kobe University, Japan"],"affiliations":[{"raw_affiliation_string":"Kobe University, Japan","institution_ids":["https://openalex.org/I65837984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048694461","display_name":"Masakatu Morii","orcid":null},"institutions":[{"id":"https://openalex.org/I65837984","display_name":"Kobe University","ror":"https://ror.org/03tgsfw79","country_code":"JP","type":"education","lineage":["https://openalex.org/I65837984"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masakatu Morii","raw_affiliation_strings":["Kobe University, Japan"],"affiliations":[{"raw_affiliation_string":"Kobe University, Japan","institution_ids":["https://openalex.org/I65837984"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5090831474"],"corresponding_institution_ids":["https://openalex.org/I65837984"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.36162653,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"136","last_page":"145"},"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":0.9997000098228455,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9900000095367432,"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":0.6052354574203491},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.49787068367004395},{"id":"https://openalex.org/keywords/internet-privacy","display_name":"Internet privacy","score":0.41314277052879333},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.3852560818195343}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6052354574203491},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.49787068367004395},{"id":"https://openalex.org/C108827166","wikidata":"https://www.wikidata.org/wiki/Q175975","display_name":"Internet privacy","level":1,"score":0.41314277052879333},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.3852560818195343}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3486622.3493939","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3486622.3493939","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3486622.3493939","source":{"id":"https://openalex.org/S4363608074","display_name":"IEEE/WIC/ACM International Conference on Web Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/WIC/ACM International Conference on Web Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3486622.3493939","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3486622.3493939","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3486622.3493939","source":{"id":"https://openalex.org/S4363608074","display_name":"IEEE/WIC/ACM International Conference on Web Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/WIC/ACM International Conference on Web Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4225586908.pdf","grobid_xml":"https://content.openalex.org/works/W4225586908.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W2102636708","https://openalex.org/W2140910804","https://openalex.org/W2141007997","https://openalex.org/W2493916176","https://openalex.org/W2531862055","https://openalex.org/W2763572884","https://openalex.org/W2786672974","https://openalex.org/W2796536780","https://openalex.org/W2810026022","https://openalex.org/W2903981179","https://openalex.org/W2906971970","https://openalex.org/W2910027323","https://openalex.org/W2913649461","https://openalex.org/W2948507959","https://openalex.org/W2951307134","https://openalex.org/W3000155280","https://openalex.org/W3022435406","https://openalex.org/W3022924198","https://openalex.org/W3031781733","https://openalex.org/W3045987077","https://openalex.org/W3126072720","https://openalex.org/W3126455143","https://openalex.org/W4251372957","https://openalex.org/W4288079542"],"related_works":["https://openalex.org/W1038206","https://openalex.org/W532702","https://openalex.org/W9774634","https://openalex.org/W6853338","https://openalex.org/W14460074","https://openalex.org/W10538934","https://openalex.org/W7972544","https://openalex.org/W1681771","https://openalex.org/W4639228","https://openalex.org/W16148550"],"abstract_inverted_index":{"The":[0],"spread":[1],"of":[2,74,121,139],"fake":[3,16,50,90,93,106,134,143],"news":[4,17,51,81,107,135,144],"on":[5,53,83],"social":[6],"networking":[7],"sites":[8],"has":[9],"become":[10],"a":[11,46],"problem.":[12],"Users":[13],"who":[14,77],"share":[15],"have":[18,35],"strong":[19],"human":[20],"needs":[21],"(such":[22],"as":[23],"the":[24,54,61,72,79,111,113,127],"desire":[25],"for":[26,48,132],"approval,":[27],"belonging,":[28],"and":[29,31,105,110,137],"self-expression)":[30],"are":[32,66,87],"likely":[33],"to":[34],"characteristic":[36],"words":[37,56,70],"in":[38,57,71,145],"their":[39],"self-descriptions.":[40,59],"In":[41,60,97],"this":[42],"paper,":[43],"we":[44,124],"propose":[45],"method":[47,115,129],"detecting":[49],"based":[52],"biased":[55],"those":[58],"proposed":[62,114,128],"method,":[63],"feature":[64],"vectors":[65],"first":[67],"created":[68],"from":[69,108],"self-descriptions":[73],"multiple":[75,101],"users":[76,140],"post":[78],"same":[80],"URL":[82],"Twitter.":[84],"Subsequently,":[85],"they":[86],"classified":[88],"into":[89],"or":[91],"not":[92],"using":[94,100],"machine":[95],"learning.":[96],"experiments":[98],"conducted":[99],"datasets,":[102],"including":[103],"real":[104],"Japan":[109],"U.S.,":[112],"achieved":[116],"an":[117],"average":[118],"classification":[119],"accuracy":[120],"90.2%.":[122],"Furthermore,":[123],"show":[125],"that":[126],"is":[130],"effective":[131],"multi-domain":[133],"detection":[136],"analysis":[138],"targeted":[141],"by":[142],"case":[146],"studies.":[147]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}