{"id":"https://openalex.org/W3111054085","doi":"https://doi.org/10.1109/smc42975.2020.9283056","title":"A Novel Approach for Cantonese Rumor Detection based on Deep Neural Network","display_name":"A Novel Approach for Cantonese Rumor Detection based on Deep Neural Network","publication_year":2020,"publication_date":"2020-10-11","ids":{"openalex":"https://openalex.org/W3111054085","doi":"https://doi.org/10.1109/smc42975.2020.9283056","mag":"3111054085"},"language":"en","primary_location":{"id":"doi:10.1109/smc42975.2020.9283056","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc42975.2020.9283056","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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/A5012246282","display_name":"Liang Ke","orcid":null},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Liang Ke","raw_affiliation_strings":["College of Cybersecurity, Sichuan University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"College of Cybersecurity, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100443901","display_name":"Xinyu Chen","orcid":"https://orcid.org/0000-0002-8046-8492"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyu Chen","raw_affiliation_strings":["College of Cybersecurity, Sichuan University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"College of Cybersecurity, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100615622","display_name":"Zhipeng Lu","orcid":"https://orcid.org/0000-0002-3852-1181"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhipeng Lu","raw_affiliation_strings":["College of Cybersecurity, Sichuan University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"College of Cybersecurity, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047623152","display_name":"Hanjian Su","orcid":"https://orcid.org/0000-0002-7983-5443"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hanjian Su","raw_affiliation_strings":["College of Cybersecurity, Sichuan University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"College of Cybersecurity, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101769227","display_name":"Haizhou Wang","orcid":"https://orcid.org/0000-0003-1197-5906"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haizhou Wang","raw_affiliation_strings":["College of Cybersecurity, Sichuan University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"College of Cybersecurity, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5012246282"],"corresponding_institution_ids":["https://openalex.org/I24185976"],"apc_list":null,"apc_paid":null,"fwci":3.6408,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.94233758,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"2020","issue":null,"first_page":"1610","last_page":"1615"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11147","display_name":"Misinformation and Its Impacts","score":0.9998000264167786,"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":0.9998000264167786,"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/T10028","display_name":"Topic Modeling","score":0.9833999872207642,"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"}},{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9740999937057495,"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/rumor","display_name":"Rumor","score":0.9926429390907288},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7604272961616516},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7089699506759644},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.504299521446228},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.5005788803100586},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4344530999660492},{"id":"https://openalex.org/keywords/order","display_name":"Order (exchange)","score":0.41032958030700684},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3403823971748352},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32310599088668823},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.17983487248420715}],"concepts":[{"id":"https://openalex.org/C2780469804","wikidata":"https://www.wikidata.org/wiki/Q878352","display_name":"Rumor","level":2,"score":0.9926429390907288},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7604272961616516},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7089699506759644},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.504299521446228},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.5005788803100586},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4344530999660492},{"id":"https://openalex.org/C182306322","wikidata":"https://www.wikidata.org/wiki/Q1779371","display_name":"Order (exchange)","level":2,"score":0.41032958030700684},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3403823971748352},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32310599088668823},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.17983487248420715},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C39549134","wikidata":"https://www.wikidata.org/wiki/Q133080","display_name":"Public relations","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/smc42975.2020.9283056","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc42975.2020.9283056","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"},{"id":"mag:3161091574","is_oa":false,"landing_page_url":"https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=202102268402975919","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1546111015","https://openalex.org/W2032897813","https://openalex.org/W2084591134","https://openalex.org/W2142869398","https://openalex.org/W2153804780","https://openalex.org/W2157331557","https://openalex.org/W2289167287","https://openalex.org/W2293652414","https://openalex.org/W2577888896","https://openalex.org/W2609512471","https://openalex.org/W2735898654","https://openalex.org/W2741930413","https://openalex.org/W2780029161","https://openalex.org/W2790166049","https://openalex.org/W2803502351","https://openalex.org/W2894665583","https://openalex.org/W2896457183","https://openalex.org/W2900892061","https://openalex.org/W2921483425","https://openalex.org/W2962739339","https://openalex.org/W2963341956","https://openalex.org/W2963626623","https://openalex.org/W2998395006","https://openalex.org/W4297730508","https://openalex.org/W6682780409","https://openalex.org/W6732431570","https://openalex.org/W6751322027","https://openalex.org/W6755207826"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2372853429","https://openalex.org/W2793319716","https://openalex.org/W3110636174","https://openalex.org/W4210503589","https://openalex.org/W2908713064","https://openalex.org/W2810386322","https://openalex.org/W2801267666","https://openalex.org/W2188429085","https://openalex.org/W2886888575"],"abstract_inverted_index":{"Twitter":[0,116],"is":[1,52,75,85,171],"a":[2,24,119,157],"popular":[3],"social":[4,32],"networking":[5],"platform.":[6],"While":[7],"people":[8],"enjoy":[9],"the":[10,46,66,90,95,198],"news":[11],"and":[12,29,111,117,135,142,185],"anecdotes":[13],"on":[14,27,71,115,177],"Twitter,":[15],"there":[16,74],"are":[17,40,58,99,137,150],"also":[18],"lots":[19],"of":[20,38,48,68,80,92,147,182],"rumors,":[21,36],"which":[22,61],"have":[23],"negative":[25],"impact":[26],"users":[28],"can":[30],"compromise":[31],"order.":[33],"Among":[34],"these":[35,148],"many":[37],"them":[39],"written":[41],"in":[42,102,144,153,205],"Cantonese.":[43,145],"At":[44],"present,":[45],"research":[47],"English":[49],"rumor":[50,123,207],"detection":[51,67,97,176,203],"relatively":[53,120],"comprehensive,":[54],"but":[55],"Cantonese":[56,69,81,104,113,122,174,191,206],"rumors":[57,70,114,141,175],"rarely":[59],"studied,":[60],"brings":[62],"great":[63],"challenges":[64],"to":[65,87,139,188],"Twitter.":[72,178],"Firstly,":[73],"no":[76],"available":[77],"benchmark":[78],"dataset":[79],"rumors.":[82,93,105,192],"Secondly,":[83],"it":[84],"difficult":[86],"completely":[88],"extract":[89],"features":[91,149,187],"Thirdly,":[94],"classical":[96],"approaches":[98],"not":[100],"effective":[101],"detecting":[103],"In":[106],"this":[107,154],"paper,":[108],"we":[109],"collected":[110],"annotated":[112],"obtained":[118],"complete":[121],"dataset.":[124],"Next,":[125],"27":[126],"statistical":[127,184],"features,":[128],"involving":[129],"four":[130],"categories":[131],"(user,":[132],"content,":[133],"propagation,":[134],"comment-based),":[136],"extracted":[138],"distinguish":[140],"non-rumors":[143],"Seven":[146],"newly":[151],"proposed":[152],"paper.":[155],"Then,":[156],"novel":[158],"deep":[159],"learning":[160],"model":[161,200],"called":[162],"BLA":[163,179,199],"(namely":[164],"BERT-based":[165],"Bi-LSTM":[166],"network":[167],"with":[168],"Attention":[169],"mechanism)":[170],"built":[172],"for":[173],"takes":[180],"advantage":[181],"both":[183],"semantic":[186],"effectively":[189],"detect":[190],"The":[193],"experimental":[194],"results":[195],"show":[196],"that":[197],"outperforms":[201],"other":[202],"models":[204],"detection.":[208]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}