{"id":"https://openalex.org/W4406458515","doi":"https://doi.org/10.1109/bigdata62323.2024.10825363","title":"Enhancing Suicide Risk Detection with a Multisource Data Filtering and Fusion Optimization Framework (MDF-FOF)","display_name":"Enhancing Suicide Risk Detection with a Multisource Data Filtering and Fusion Optimization Framework (MDF-FOF)","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4406458515","doi":"https://doi.org/10.1109/bigdata62323.2024.10825363"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata62323.2024.10825363","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825363","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/A5115940095","display_name":"Zheng Shouwen","orcid":null},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":true,"raw_author_name":"Zheng Shouwen","raw_affiliation_strings":["The Hong Kong Polytechnic University,Department of Computing,Hong Kong"],"affiliations":[{"raw_affiliation_string":"The Hong Kong Polytechnic University,Department of Computing,Hong Kong","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115940096","display_name":"Zhou Taiqi","orcid":null},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Zhou Taiqi","raw_affiliation_strings":["The Hong Kong Polytechnic University,Department of Computing,Hong Kong"],"affiliations":[{"raw_affiliation_string":"The Hong Kong Polytechnic University,Department of Computing,Hong Kong","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115940097","display_name":"Tao Yingzhi","orcid":null},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Yingzhi","raw_affiliation_strings":["Anhui University,School of Computer Science and Technology"],"affiliations":[{"raw_affiliation_string":"Anhui University,School of Computer Science and Technology","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115940098","display_name":"Chen Junru","orcid":null},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Chen Junru","raw_affiliation_strings":["The Hong Kong Polytechnic University,Department of Computing,Hong Kong"],"affiliations":[{"raw_affiliation_string":"The Hong Kong Polytechnic University,Department of Computing,Hong Kong","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029875220","display_name":"Ruofei Wang","orcid":"https://orcid.org/0000-0003-0605-9663"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Wang Ruofei","raw_affiliation_strings":["The Hong Kong Polytechnic University,Department of Marketing and Management,Hong Kong"],"affiliations":[{"raw_affiliation_string":"The Hong Kong Polytechnic University,Department of Marketing and Management,Hong Kong","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100406645","display_name":"Siyuan Liu","orcid":"https://orcid.org/0000-0003-3661-6248"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Liu Siyuan","raw_affiliation_strings":["The Hong Kong Polytechnic University,Department of Computing,Hong Kong"],"affiliations":[{"raw_affiliation_string":"The Hong Kong Polytechnic University,Department of Computing,Hong Kong","institution_ids":["https://openalex.org/I14243506"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5115940095"],"corresponding_institution_ids":["https://openalex.org/I14243506"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.23730427,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"8581","last_page":"8590"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9940999746322632,"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"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9940999746322632,"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/T12488","display_name":"Mental Health via Writing","score":0.9919000267982483,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9739000201225281,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.7213655710220337},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.602525532245636},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.5051351189613342},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39880630373954773},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3385113477706909}],"concepts":[{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.7213655710220337},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.602525532245636},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.5051351189613342},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39880630373954773},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3385113477706909},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata62323.2024.10825363","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825363","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":[{"id":"https://metadata.un.org/sdg/5","display_name":"Gender equality","score":0.4000000059604645}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2936503027","https://openalex.org/W2965373594","https://openalex.org/W3136343621","https://openalex.org/W3155707196","https://openalex.org/W4214653173","https://openalex.org/W4309633540","https://openalex.org/W4313421210","https://openalex.org/W4324030804","https://openalex.org/W4385606438","https://openalex.org/W4392462069","https://openalex.org/W6766673545"],"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/W2132659060","https://openalex.org/W2031992971","https://openalex.org/W3214791684","https://openalex.org/W2152662039"],"abstract_inverted_index":{"Recently,":[0],"with":[1,72,102],"the":[2,8,60,114,118,122,133,167],"popularity":[3],"of":[4,62,84,117,163],"social":[5,43],"media":[6,44],"platforms,":[7],"increase":[9],"in":[10,42,146,166],"suicide-related":[11],"content":[12],"has":[13],"triggered":[14],"great":[15],"attention":[16],"on":[17,32,121,148],"automated":[18],"suicide":[19,40],"risk":[20],"detection":[21],"systems.":[22],"This":[23,153],"research":[24],"proposes":[25],"a":[26,49,67,77,89,103,156],"natural":[27],"language":[28,69],"processing":[29],"model":[30,70,85],"based":[31],"RoBERTa,":[33],"which":[34,57,129],"aims":[35],"to":[36,75],"identify":[37],"and":[38,53,99,136,143],"classify":[39],"risks":[41],"posts.":[45],"Our":[46],"team":[47],"propose":[48],"\"Multisource":[50],"data":[51,63],"filtering":[52],"fusion":[54],"optimization":[55],"framework\"(MDF-FOF),":[56],"effectively":[58],"solves":[59],"problem":[61],"imbalance":[64],"by":[65],"combining":[66],"large":[68],"(LLM)":[71],"manual":[73],"annotation":[74],"generate":[76],"balanced":[78],"training":[79],"sample":[80],"set.":[81],"In":[82],"terms":[83],"construction,":[86],"we":[87],"proposed":[88,119],"framework":[90,120,159],"MDF-FOF":[91],"that":[92,113],"utilizes":[93],"pre-trained":[94],"RoBERTa":[95],"for":[96,106,160],"feature":[97],"extraction":[98,162],"combines":[100],"it":[101],"self-built":[104],"EmoBERT":[105],"soft":[107],"label":[108],"classification.":[109],"Experimental":[110],"results":[111],"show":[112],"recall":[115],"rate":[116],"validation":[123],"set":[124],"is":[125,130],"stable":[126],"above":[127],"0.75,":[128],"better":[131],"than":[132],"existing":[134],"methods":[135],"baseline":[137],"models.":[138],"It":[139],"shows":[140],"good":[141],"robustness":[142],"excellent":[144],"performance":[145],"tests":[147],"datasets":[149],"from":[150],"different":[151],"sources.":[152],"study":[154],"provides":[155],"reliable":[157],"basic":[158],"multi-feature":[161],"user":[164],"posts":[165],"future.":[168]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}