{"id":"https://openalex.org/W3042196038","doi":"https://doi.org/10.24963/ijcai.2020/760","title":"BlueMemo: Depression Analysis through Twitter Posts","display_name":"BlueMemo: Depression Analysis through Twitter Posts","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3042196038","doi":"https://doi.org/10.24963/ijcai.2020/760","mag":"3042196038"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2020/760","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2020/760","pdf_url":"https://www.ijcai.org/proceedings/2020/0760.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2020/0760.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5078808331","display_name":"Pengwei Hu","orcid":"https://orcid.org/0000-0001-5974-7932"},"institutions":[{"id":"https://openalex.org/I4210113516","display_name":"IBM Research - Brazil","ror":"https://ror.org/01fxqdx25","country_code":"BR","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210113516","https://openalex.org/I4210114115"]},{"id":"https://openalex.org/I4210126794","display_name":"IBM Research (China)","ror":"https://ror.org/02yg1pf55","country_code":"CN","type":"company","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115","https://openalex.org/I4210126794"]}],"countries":["BR","CN"],"is_corresponding":false,"raw_author_name":"Pengwei Hu","raw_affiliation_strings":["IBM Resaearch","IBM Research, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Resaearch","institution_ids":["https://openalex.org/I4210113516"]},{"raw_affiliation_string":"IBM Research, China","institution_ids":["https://openalex.org/I4210126794"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046723920","display_name":"Chenhao Lin","orcid":"https://orcid.org/0000-0002-6265-7345"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenhao Lin","raw_affiliation_strings":["Xi\u2019an Jiaotong University","Xi'an Jiaotong University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi\u2019an Jiaotong University","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"Xi'an Jiaotong University, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064445567","display_name":"Hui Su","orcid":"https://orcid.org/0000-0003-0340-1128"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hui Su","raw_affiliation_strings":["Wechat, Tencent","Pattern Recognition Center, Wechat AI, Tencent Inc, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wechat, Tencent","institution_ids":["https://openalex.org/I2250653659"]},{"raw_affiliation_string":"Pattern Recognition Center, Wechat AI, Tencent Inc, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082243346","display_name":"Shao\u2010Chun Li","orcid":"https://orcid.org/0000-0001-9818-4255"},"institutions":[{"id":"https://openalex.org/I4210126794","display_name":"IBM Research (China)","ror":"https://ror.org/02yg1pf55","country_code":"CN","type":"company","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115","https://openalex.org/I4210126794"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaochun Li","raw_affiliation_strings":["IBM Research","IBM Watson Health, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research","institution_ids":[]},{"raw_affiliation_string":"IBM Watson Health, China","institution_ids":["https://openalex.org/I4210126794"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100627392","display_name":"Xue Han","orcid":"https://orcid.org/0000-0003-3896-4609"},"institutions":[{"id":"https://openalex.org/I4210126794","display_name":"IBM Research (China)","ror":"https://ror.org/02yg1pf55","country_code":"CN","type":"company","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115","https://openalex.org/I4210126794"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xue Han","raw_affiliation_strings":["IBM Research","IBM Research, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research","institution_ids":[]},{"raw_affiliation_string":"IBM Research, China","institution_ids":["https://openalex.org/I4210126794"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067423633","display_name":"Yuan Zhang","orcid":"https://orcid.org/0000-0003-3783-7974"},"institutions":[{"id":"https://openalex.org/I4210126794","display_name":"IBM Research (China)","ror":"https://ror.org/02yg1pf55","country_code":"CN","type":"company","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115","https://openalex.org/I4210126794"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Zhang","raw_affiliation_strings":["IBM Research","IBM Research, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research","institution_ids":[]},{"raw_affiliation_string":"IBM Research, China","institution_ids":["https://openalex.org/I4210126794"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101682159","display_name":"Jing Mei","orcid":"https://orcid.org/0000-0002-5179-5128"},"institutions":[{"id":"https://openalex.org/I4210126794","display_name":"IBM Research (China)","ror":"https://ror.org/02yg1pf55","country_code":"CN","type":"company","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115","https://openalex.org/I4210126794"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Mei","raw_affiliation_strings":["IBM Research","IBM Research, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research","institution_ids":[]},{"raw_affiliation_string":"IBM Research, China","institution_ids":["https://openalex.org/I4210126794"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.8513,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.85789902,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"5252","last_page":"5254"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12488","display_name":"Mental Health via Writing","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T12488","display_name":"Mental Health via Writing","score":0.9998999834060669,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9958000183105469,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.973800003528595,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.7561208009719849},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.7299617528915405},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6333101391792297},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.5554505586624146},{"id":"https://openalex.org/keywords/depression","display_name":"Depression (economics)","score":0.5211051106452942},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.4661993086338043},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.44279319047927856},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.34783387184143066},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3351026177406311},{"id":"https://openalex.org/keywords/internet-privacy","display_name":"Internet privacy","score":0.3350822329521179},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.32308492064476013},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.30912697315216064},{"id":"https://openalex.org/keywords/sociology","display_name":"Sociology","score":0.07683113217353821}],"concepts":[{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.7561208009719849},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.7299617528915405},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6333101391792297},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.5554505586624146},{"id":"https://openalex.org/C2776867660","wikidata":"https://www.wikidata.org/wiki/Q1814941","display_name":"Depression (economics)","level":2,"score":0.5211051106452942},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.4661993086338043},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.44279319047927856},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.34783387184143066},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3351026177406311},{"id":"https://openalex.org/C108827166","wikidata":"https://www.wikidata.org/wiki/Q175975","display_name":"Internet privacy","level":1,"score":0.3350822329521179},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.32308492064476013},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30912697315216064},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.07683113217353821},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C139719470","wikidata":"https://www.wikidata.org/wiki/Q39680","display_name":"Macroeconomics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2020/760","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2020/760","pdf_url":"https://www.ijcai.org/proceedings/2020/0760.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2020/760","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2020/760","pdf_url":"https://www.ijcai.org/proceedings/2020/0760.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.5299999713897705,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3042196038.pdf","grobid_xml":"https://content.openalex.org/works/W3042196038.grobid-xml"},"referenced_works_count":17,"referenced_works":["https://openalex.org/W1600774825","https://openalex.org/W1861492603","https://openalex.org/W2053290822","https://openalex.org/W2297358007","https://openalex.org/W2604402455","https://openalex.org/W2611167769","https://openalex.org/W2740966010","https://openalex.org/W2786036168","https://openalex.org/W2807110764","https://openalex.org/W2807151223","https://openalex.org/W2807710762","https://openalex.org/W2896457183","https://openalex.org/W2905587047","https://openalex.org/W2963341956","https://openalex.org/W2964346351","https://openalex.org/W2964478555","https://openalex.org/W4367608470"],"related_works":["https://openalex.org/W2185469136","https://openalex.org/W2032233321","https://openalex.org/W2011264131","https://openalex.org/W3121970507","https://openalex.org/W2110028391","https://openalex.org/W54497855","https://openalex.org/W217960748","https://openalex.org/W3125814499","https://openalex.org/W4301143707","https://openalex.org/W2952745240"],"abstract_inverted_index":{"The":[0,116],"use":[1],"of":[2,37,74],"social":[3,21,26,71],"media":[4,27,72],"runs":[5],"through":[6],"our":[7,114],"lives,":[8],"and":[9,23,53,94,102,109,125,128],"users'":[10],"emotions":[11],"are":[12],"also":[13],"affected":[14],"by":[15,40],"it.":[16],"Previous":[17],"studies":[18],"have":[19],"reported":[20],"organizations":[22],"psychologists":[24],"using":[25],"to":[28,34,48,112,122],"find":[29],"depressed":[30,75],"patients.":[31],"However,":[32],"due":[33],"the":[35,46,50,55,59,87,120],"variety":[36],"content":[38],"published":[39],"users,":[41],"it":[42],"isn't":[43],"effortless":[44],"for":[45,70,135],"system":[47,69],"consider":[49],"text,":[51],"image,":[52],"even":[54],"hidden":[56],"information":[57],"behind":[58],"image.":[60],"To":[61],"address":[62],"this":[63],"problem,":[64],"we":[65],"proposed":[66,117],"a":[67,106],"new":[68],"screening":[73],"patients":[76],"named":[77],"BlueMemo.":[78],"We":[79],"collected":[80],"real-time":[81],"posts":[82],"from":[83],"Twitter.":[84],"Based":[85],"on":[86],"posts,":[88],"learned":[89],"text":[90],"features,":[91,93],"image":[92],"visual":[95],"attributes":[96],"were":[97,103],"extracted":[98],"as":[99],"three":[100],"modalities":[101],"fed":[104],"into":[105],"multi-modal":[107],"fusion":[108],"classification":[110],"model":[111],"implement":[113],"system.":[115],"BlueMemo":[118],"has":[119],"power":[121],"help":[123],"physicians":[124],"clinicians":[126],"quickly":[127],"accurately":[129],"identify":[130],"users":[131],"at":[132],"potential":[133],"risk":[134],"depression.":[136]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}