{"id":"https://openalex.org/W4321480032","doi":"https://doi.org/10.1145/3539597.3570462","title":"Combining vs. Transferring Knowledge: Investigating Strategies for Improving Demographic Inference in Low Resource Settings","display_name":"Combining vs. Transferring Knowledge: Investigating Strategies for Improving Demographic Inference in Low Resource Settings","publication_year":2023,"publication_date":"2023-02-22","ids":{"openalex":"https://openalex.org/W4321480032","doi":"https://doi.org/10.1145/3539597.3570462"},"language":"en","primary_location":{"id":"doi:10.1145/3539597.3570462","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3539597.3570462","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining","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/A5067240869","display_name":"Yaguang Liu","orcid":"https://orcid.org/0000-0002-1926-444X"},"institutions":[{"id":"https://openalex.org/I184565670","display_name":"Georgetown University","ror":"https://ror.org/05vzafd60","country_code":"US","type":"education","lineage":["https://openalex.org/I184565670"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yaguang Liu","raw_affiliation_strings":["Georgetown University, Washington, DC, USA"],"affiliations":[{"raw_affiliation_string":"Georgetown University, Washington, DC, USA","institution_ids":["https://openalex.org/I184565670"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005384315","display_name":"Lisa Singh","orcid":"https://orcid.org/0000-0002-8300-2970"},"institutions":[{"id":"https://openalex.org/I184565670","display_name":"Georgetown University","ror":"https://ror.org/05vzafd60","country_code":"US","type":"education","lineage":["https://openalex.org/I184565670"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lisa Singh","raw_affiliation_strings":["Georgetown University, Washington, DC, USA"],"affiliations":[{"raw_affiliation_string":"Georgetown University, Washington, DC, USA","institution_ids":["https://openalex.org/I184565670"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5067240869"],"corresponding_institution_ids":["https://openalex.org/I184565670"],"apc_list":null,"apc_paid":null,"fwci":0.6438,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.69635852,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"868","last_page":"876"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11819","display_name":"Data-Driven Disease Surveillance","score":0.9690999984741211,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11819","display_name":"Data-Driven Disease Surveillance","score":0.9690999984741211,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.95660001039505,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"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":0.9442999958992004,"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":0.7792047262191772},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.7466994524002075},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.7436264157295227},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5829448699951172},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5781139731407166},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5613674521446228},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.5600646734237671},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5461134314537048},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.5164792537689209},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.47406214475631714},{"id":"https://openalex.org/keywords/multi-task-learning","display_name":"Multi-task learning","score":0.4515185058116913},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.43983593583106995},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4266570210456848},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.41738301515579224},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3709723949432373}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7792047262191772},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.7466994524002075},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7436264157295227},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5829448699951172},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5781139731407166},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5613674521446228},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.5600646734237671},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5461134314537048},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.5164792537689209},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.47406214475631714},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.4515185058116913},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.43983593583106995},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4266570210456848},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.41738301515579224},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3709723949432373},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3539597.3570462","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3539597.3570462","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","score":0.4099999964237213,"display_name":"Decent work and economic growth"}],"awards":[{"id":"https://openalex.org/G567173001","display_name":null,"funder_award_id":"1934925, 1934494","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1892382968","https://openalex.org/W2183341477","https://openalex.org/W2741226448","https://openalex.org/W2741616044","https://openalex.org/W2907211712","https://openalex.org/W2911735741","https://openalex.org/W2952230191","https://openalex.org/W2962678461","https://openalex.org/W2962843773","https://openalex.org/W2964199361","https://openalex.org/W2964352358","https://openalex.org/W2990761674","https://openalex.org/W3098124506","https://openalex.org/W3135302781","https://openalex.org/W3162914109","https://openalex.org/W3165711611","https://openalex.org/W3180895563","https://openalex.org/W3183212227","https://openalex.org/W3210726092"],"related_works":["https://openalex.org/W2821676139","https://openalex.org/W3043695725","https://openalex.org/W4382138864","https://openalex.org/W4387770285","https://openalex.org/W3022215768","https://openalex.org/W3135975972","https://openalex.org/W3016888008","https://openalex.org/W4385864216","https://openalex.org/W3171384686","https://openalex.org/W4387183713"],"abstract_inverted_index":{"For":[0],"some":[1],"learning":[2,147],"tasks,":[3],"generating":[4],"a":[5,124,127],"large":[6],"labeled":[7,72,129],"data":[8,17,35,38,64,74,77,95,104,130,137,163],"set":[9,96],"is":[10,18,87,92],"impractical.":[11],"Demographic":[12],"inference":[13,52],"using":[14,53],"social":[15,54],"media":[16,55],"one":[19],"such":[20],"task.":[21],"While":[22],"different":[23],"strategies":[24],"have":[25,41],"been":[26,43],"proposed":[27,158],"to":[28,82,106],"mitigate":[29],"this":[30],"challenge,":[31],"including":[32],"transfer":[33,67,119,146],"learning,":[34,120],"augmentation,":[36],"and":[37,66,89,139,154],"combination,":[39],"they":[40],"not":[42],"explored":[44],"for":[45],"the":[46,85,100,109,112,133,145,152,157],"task":[47],"of":[48,61,79,111,144,156],"user":[49],"level":[50],"demographic":[51],"data.":[56],"This":[57],"paper":[58],"explores":[59],"two":[60],"these":[62],"strategies:":[63],"combination":[65,86,113],"learning.":[68],"First,":[69],"we":[70,98,116,122],"combine":[71],"training":[73],"from":[75],"multiple":[76,161],"sets":[78,105],"similar":[80],"size":[81],"understand":[83],"when":[84,90],"valuable":[88],"it":[91],"not.":[93],"Using":[94],"distance,":[97],"quantify":[99],"relationship":[101],"between":[102],"our":[103],"help":[107],"explain":[108],"performance":[110],"strategy.":[114],"Then,":[115],"consider":[117],"supervised":[118],"where":[121],"pretrain":[123],"model":[125,134],"on":[126,135,160],"larger":[128],"set,":[131],"fine-tune":[132],"smaller":[136],"sets,":[138],"incorporate":[140],"regularization":[141],"as":[142],"part":[143],"process.":[148],"We":[149],"empirically":[150],"show":[151],"strengths":[153],"limitations":[155],"techniques":[159],"Twitter":[162],"sets.":[164]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
