{"id":"https://openalex.org/W3093561817","doi":"https://doi.org/10.1109/asonam49781.2020.9381480","title":"Unsupervised and Interpretable Domain Adaptation to Rapidly Filter Tweets for Emergency Services","display_name":"Unsupervised and Interpretable Domain Adaptation to Rapidly Filter Tweets for Emergency Services","publication_year":2020,"publication_date":"2020-12-07","ids":{"openalex":"https://openalex.org/W3093561817","doi":"https://doi.org/10.1109/asonam49781.2020.9381480","mag":"3093561817"},"language":"en","primary_location":{"id":"doi:10.1109/asonam49781.2020.9381480","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asonam49781.2020.9381480","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2003.04991","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5088184093","display_name":"Jitin Krishnan","orcid":null},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jitin Krishnan","raw_affiliation_strings":["Department of Computer Science, George Mason University, Fairfax, VA, USA","#N#George Mason University#N#"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, George Mason University, Fairfax, VA, USA","institution_ids":["https://openalex.org/I162714631"]},{"raw_affiliation_string":"#N#George Mason University#N#","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012073624","display_name":"Hemant Purohit","orcid":"https://orcid.org/0000-0002-4573-8450"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hemant Purohit","raw_affiliation_strings":["Department of Information Sciences & Technology, George Mason University, Fairfax, VA, USA","#N#George Mason University#N#"],"affiliations":[{"raw_affiliation_string":"Department of Information Sciences & Technology, George Mason University, Fairfax, VA, USA","institution_ids":["https://openalex.org/I162714631"]},{"raw_affiliation_string":"#N#George Mason University#N#","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006581225","display_name":"Huzefa Rangwala","orcid":"https://orcid.org/0000-0003-0435-0035"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Huzefa Rangwala","raw_affiliation_strings":["Department of Computer Science, George Mason University, Fairfax, VA, USA","#N#George Mason University#N#"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, George Mason University, Fairfax, VA, USA","institution_ids":["https://openalex.org/I162714631"]},{"raw_affiliation_string":"#N#George Mason University#N#","institution_ids":["https://openalex.org/I162714631"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5088184093"],"corresponding_institution_ids":["https://openalex.org/I162714631"],"apc_list":null,"apc_paid":null,"fwci":0.1359,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.56972195,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"409","last_page":"416"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9987000226974487,"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/T10028","display_name":"Topic Modeling","score":0.9987000226974487,"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/T13018","display_name":"Seismology and Earthquake Studies","score":0.9927999973297119,"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/T11147","display_name":"Misinformation and Its Impacts","score":0.9898999929428101,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.81397545337677},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7856799364089966},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5843505859375},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5530616641044617},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5120781064033508},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.4587116837501526},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.45775094628334045},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4401555061340332},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.43257665634155273},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.42582184076309204},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4141589105129242},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.33306795358657837}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.81397545337677},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7856799364089966},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5843505859375},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5530616641044617},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5120781064033508},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.4587116837501526},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.45775094628334045},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4401555061340332},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.43257665634155273},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.42582184076309204},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4141589105129242},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.33306795358657837},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/asonam49781.2020.9381480","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asonam49781.2020.9381480","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2003.04991","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2003.04991","pdf_url":"https://arxiv.org/pdf/2003.04991","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:3093561817","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2003.04991","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2003.04991","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2003.04991","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2003.04991","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2003.04991","pdf_url":"https://arxiv.org/pdf/2003.04991","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3093561817.pdf","grobid_xml":"https://content.openalex.org/works/W3093561817.grobid-xml"},"referenced_works_count":62,"referenced_works":["https://openalex.org/W32256312","https://openalex.org/W168564468","https://openalex.org/W582055897","https://openalex.org/W1731081199","https://openalex.org/W1832693441","https://openalex.org/W1847088711","https://openalex.org/W1902237438","https://openalex.org/W1968194983","https://openalex.org/W1981048805","https://openalex.org/W2064675550","https://openalex.org/W2101234009","https://openalex.org/W2130942839","https://openalex.org/W2131774270","https://openalex.org/W2131953535","https://openalex.org/W2139188905","https://openalex.org/W2145094598","https://openalex.org/W2153353890","https://openalex.org/W2153579005","https://openalex.org/W2158108973","https://openalex.org/W2163302275","https://openalex.org/W2227904035","https://openalex.org/W2250539671","https://openalex.org/W2250734828","https://openalex.org/W2282821441","https://openalex.org/W2295072214","https://openalex.org/W2297338375","https://openalex.org/W2493475353","https://openalex.org/W2511201422","https://openalex.org/W2516809705","https://openalex.org/W2519911434","https://openalex.org/W2606327720","https://openalex.org/W2617039999","https://openalex.org/W2624871570","https://openalex.org/W2741989495","https://openalex.org/W2753193937","https://openalex.org/W2898274636","https://openalex.org/W2898454117","https://openalex.org/W2913340405","https://openalex.org/W2949541494","https://openalex.org/W2949821452","https://openalex.org/W2962707464","https://openalex.org/W2962772361","https://openalex.org/W2963261224","https://openalex.org/W2963826681","https://openalex.org/W2964250510","https://openalex.org/W2964308564","https://openalex.org/W2969206604","https://openalex.org/W3135184420","https://openalex.org/W3152368098","https://openalex.org/W6637618735","https://openalex.org/W6638824847","https://openalex.org/W6675354045","https://openalex.org/W6679436768","https://openalex.org/W6681096077","https://openalex.org/W6682691769","https://openalex.org/W6684149856","https://openalex.org/W6697316661","https://openalex.org/W6713239141","https://openalex.org/W6738491513","https://openalex.org/W6747248625","https://openalex.org/W6774258431","https://openalex.org/W6793575156"],"related_works":["https://openalex.org/W3011474921","https://openalex.org/W3034314572","https://openalex.org/W2982389186","https://openalex.org/W3080670519","https://openalex.org/W3201401944","https://openalex.org/W2511201422","https://openalex.org/W2909566100","https://openalex.org/W2964905055","https://openalex.org/W2068965752","https://openalex.org/W2753193937","https://openalex.org/W3019470236","https://openalex.org/W2905564348","https://openalex.org/W2788509344","https://openalex.org/W3090855069","https://openalex.org/W2907375036","https://openalex.org/W3176020109","https://openalex.org/W3162400235","https://openalex.org/W2904389022","https://openalex.org/W2948073857","https://openalex.org/W2940792992"],"abstract_inverted_index":{"During":[0],"the":[1,42,95,197,241,247,253,261,269,280,291,295,305,322],"onset":[2,97],"of":[3,48,98,151,200,227,264,290,314],"a":[4,78,99,104,131,136,182,276,298,311,319],"natural":[5],"or":[6],"man-made":[7],"crisis":[8,86,115,140,219,231],"event,":[9],"public":[10,198],"often":[11],"share":[12],"relevant":[13,28,49,109,211],"information":[14,91],"for":[15,88,139,155,163,185,230,287,321],"emergency":[16,285],"services":[17,286],"on":[18,246],"social":[19,35,110],"web":[20],"platforms":[21],"such":[22,27,221],"as":[23,222,240,275],"Twitter.":[24],"However,":[25],"filtering":[26,92],"data":[29,59,83,120],"in":[30,55,297,304],"real-time":[31],"at":[32],"scale":[33],"using":[34],"media":[36],"mining":[37],"is":[38,194,233],"challenging":[39],"due":[40],"to":[41,81,107,158,278],"short":[43],"noisy":[44],"text,":[45],"sparse":[46,171],"availability":[47],"data,":[50],"and":[51,188,224,244,283],"also,":[52],"practical":[53,312],"limitations":[54],"collecting":[56],"large":[57],"labeled":[58,206],"during":[60,94,112],"an":[61,113],"ongoing":[62,114],"event.":[63],"In":[64],"this":[65,122,176],"paper,":[66],"we":[67,129,173,266,309],"hypothesize":[68],"that":[69,175,204,252,268,300],"unsupervised":[70,125],"domain":[71,126,143,189,228],"adaptation":[72,229],"through":[73],"multi-task":[74,133,142,254],"learning":[75,187],"can":[76,177,272],"be":[77,178,273],"useful":[79],"framework":[80,193],"leverage":[82],"from":[84,121],"past":[85],"events":[87,220,232],"training":[89,245],"efficient":[90],"models":[93],"sudden":[96],"new":[100,119],"crisis.":[101],"We":[102],"present":[103],"novel":[105],"method":[106],"classify":[108],"posts":[111,208],"without":[116],"seeing":[117],"any":[118],"event":[123,239],"(fully":[124],"adaptation).":[127],"Specifically,":[128],"construct":[130],"customized":[132],"architecture":[134],"with":[135,170,196,210],"multi-domain":[137],"discriminator":[138],"analytics:":[141],"adversarial":[144,190],"attention":[145,153,270],"network":[146],"(MT-DAAN).":[147],"This":[148],"model":[149,160,255,281],"consists":[150],"dedicated":[152],"layers":[154],"each":[156],"task":[157],"provide":[159,205],"interpretability;":[161],"critical":[162],"real-word":[164],"applications.":[165],"As":[166],"deep":[167],"networks":[168],"struggle":[169],"datasets,":[172],"show":[174,251,267,310],"improved":[179],"by":[180,235,293,317],"sharing":[181],"base":[183],"layer":[184,271],"multitask":[186],"training.":[191],"The":[192],"validated":[195],"datasets":[199],"TREC":[201],"incident":[202],"streams":[203],"Twitter":[207],"(tweets)":[209],"classes":[212],"(Priority,":[213],"Factoid,":[214],"Sentiment)":[215],"across":[216],"10":[217],"different":[218],"floods":[223],"earthquakes.":[225],"Evaluation":[226],"performed":[234],"choosing":[236],"one":[237],"target":[238],"test":[242],"set":[243],"rest.":[248],"Our":[249],"results":[250],"outperformed":[256],"its":[257],"single-task":[258],"counterpart.":[259],"For":[260],"qualitative":[262],"evaluation":[263],"interpretability,":[265],"used":[274],"guide":[277],"explain":[279],"predictions":[282],"empower":[284],"exploring":[288],"accountability":[289],"model,":[292],"showcasing":[294],"words":[296],"tweet":[299],"are":[301],"deemed":[302],"important":[303],"classification":[306],"process.":[307],"Finally,":[308],"implication":[313],"our":[315],"work":[316],"providing":[318],"use-case":[320],"COVID-19":[323],"pandemic.":[324]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-04-09T06:08:40.794217","created_date":"2022-07-26T00:00:00"}