{"id":"https://openalex.org/W2045515072","doi":"https://doi.org/10.1145/2642918.2647367","title":"Glance","display_name":"Glance","publication_year":2014,"publication_date":"2014-10-01","ids":{"openalex":"https://openalex.org/W2045515072","doi":"https://doi.org/10.1145/2642918.2647367","mag":"2045515072"},"language":"en","primary_location":{"id":"doi:10.1145/2642918.2647367","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2642918.2647367","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th annual ACM symposium on User interface software and technology","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/A5063574664","display_name":"Walter S. Lasecki","orcid":null},"institutions":[{"id":"https://openalex.org/I5388228","display_name":"University of Rochester","ror":"https://ror.org/022kthw22","country_code":"US","type":"education","lineage":["https://openalex.org/I5388228"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Walter S. Lasecki","raw_affiliation_strings":["University of Rochester, Rochester, NY, USA"],"affiliations":[{"raw_affiliation_string":"University of Rochester, Rochester, NY, USA","institution_ids":["https://openalex.org/I5388228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026198819","display_name":"Mitchell Gordon","orcid":"https://orcid.org/0000-0003-1008-2321"},"institutions":[{"id":"https://openalex.org/I5388228","display_name":"University of Rochester","ror":"https://ror.org/022kthw22","country_code":"US","type":"education","lineage":["https://openalex.org/I5388228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mitchell Gordon","raw_affiliation_strings":["University of Rochester, Rochester, NY, USA"],"affiliations":[{"raw_affiliation_string":"University of Rochester, Rochester, NY, USA","institution_ids":["https://openalex.org/I5388228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015996266","display_name":"Danai Koutra","orcid":"https://orcid.org/0000-0002-3206-8179"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Danai Koutra","raw_affiliation_strings":["Carnegie Mellon University, Pittsburgh, PA, USA"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069608785","display_name":"Malte Jung","orcid":"https://orcid.org/0000-0001-9359-7122"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Malte F. Jung","raw_affiliation_strings":["Cornell University, Ithaca, NY, USA"],"affiliations":[{"raw_affiliation_string":"Cornell University, Ithaca, NY, USA","institution_ids":["https://openalex.org/I205783295"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051426773","display_name":"Steven P. Dow","orcid":"https://orcid.org/0000-0002-1354-9866"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Steven P. Dow","raw_affiliation_strings":["Carnegie Mellon University, Pittsburgh, PA, USA"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082603621","display_name":"Jeffrey P. Bigham","orcid":"https://orcid.org/0000-0002-2072-0625"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jeffrey P. Bigham","raw_affiliation_strings":["Carnegie Mellon University, Pittsburgh, PA, USA"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5063574664"],"corresponding_institution_ids":["https://openalex.org/I5388228"],"apc_list":null,"apc_paid":null,"fwci":16.8847,"has_fulltext":false,"cited_by_count":81,"citation_normalized_percentile":{"value":0.99002355,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"551","last_page":"562"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.996399998664856,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.989799976348877,"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":0.8448998928070068},{"id":"https://openalex.org/keywords/conversation","display_name":"Conversation","score":0.582486629486084},{"id":"https://openalex.org/keywords/ambiguity","display_name":"Ambiguity","score":0.5655248761177063},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.5543757677078247},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5260080099105835},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.523623526096344},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4984304904937744},{"id":"https://openalex.org/keywords/crowds","display_name":"Crowds","score":0.44188278913497925},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3762351870536804},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.3677402436733246},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3643726110458374},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34439414739608765}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8448998928070068},{"id":"https://openalex.org/C2777200299","wikidata":"https://www.wikidata.org/wiki/Q52943","display_name":"Conversation","level":2,"score":0.582486629486084},{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.5655248761177063},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.5543757677078247},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5260080099105835},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.523623526096344},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4984304904937744},{"id":"https://openalex.org/C2777852691","wikidata":"https://www.wikidata.org/wiki/Q13430821","display_name":"Crowds","level":2,"score":0.44188278913497925},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3762351870536804},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3677402436733246},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3643726110458374},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34439414739608765},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2642918.2647367","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2642918.2647367","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th annual ACM symposium on User interface software and technology","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7099999785423279,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G3180334615","display_name":null,"funder_award_id":"#IIS-1149709","funder_id":"https://openalex.org/F4320337389","funder_display_name":"Division of Information and Intelligent Systems"},{"id":"https://openalex.org/G8334834170","display_name":null,"funder_award_id":"Ph.D. Fellowship","funder_id":"https://openalex.org/F4320307764","funder_display_name":"Microsoft"},{"id":"https://openalex.org/G8595836885","display_name":null,"funder_award_id":"#IIS-1208382","funder_id":"https://openalex.org/F4320337389","funder_display_name":"Division of Information and Intelligent Systems"}],"funders":[{"id":"https://openalex.org/F4320307764","display_name":"Microsoft","ror":"https://ror.org/00d0nc645"},{"id":"https://openalex.org/F4320337389","display_name":"Division of Information and Intelligent Systems","ror":"https://ror.org/053a2cp42"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W9014458","https://openalex.org/W1506491340","https://openalex.org/W1525984028","https://openalex.org/W1538186073","https://openalex.org/W1667831672","https://openalex.org/W1972034440","https://openalex.org/W1974665264","https://openalex.org/W1975879668","https://openalex.org/W2003281274","https://openalex.org/W2021097538","https://openalex.org/W2029202094","https://openalex.org/W2036625304","https://openalex.org/W2037187099","https://openalex.org/W2043032678","https://openalex.org/W2050383463","https://openalex.org/W2053154970","https://openalex.org/W2053907973","https://openalex.org/W2058317905","https://openalex.org/W2058556535","https://openalex.org/W2063790518","https://openalex.org/W2080951892","https://openalex.org/W2081038469","https://openalex.org/W2088664555","https://openalex.org/W2090048052","https://openalex.org/W2093522395","https://openalex.org/W2101658911","https://openalex.org/W2103802799","https://openalex.org/W2114100913","https://openalex.org/W2116680608","https://openalex.org/W2127008633","https://openalex.org/W2138847321","https://openalex.org/W2161299247","https://openalex.org/W2163986367","https://openalex.org/W2294566554","https://openalex.org/W2913879771","https://openalex.org/W2992349480","https://openalex.org/W3125092501","https://openalex.org/W4285719527","https://openalex.org/W6670603210"],"related_works":["https://openalex.org/W4240200267","https://openalex.org/W1511510665","https://openalex.org/W1524661185","https://openalex.org/W2078823605","https://openalex.org/W2500095415","https://openalex.org/W4233026749","https://openalex.org/W2097922264","https://openalex.org/W2282342021","https://openalex.org/W1516679419","https://openalex.org/W190396239"],"abstract_inverted_index":{"Behavioral":[0],"researchers":[1,30],"spend":[2],"considerable":[3],"amount":[4],"of":[5,52,73,105,141,147,157],"time":[6],"coding":[7,159],"video":[8,38,75,106,150,217],"data":[9,208],"to":[10,31,46,60,121,176,191,201],"systematically":[11],"extract":[12],"meaning":[13],"from":[14],"subtle":[15],"human":[16],"actions":[17],"and":[18,35,65,88,116,132,152,184,189],"emotions.":[19],"In":[20],"this":[21],"paper,":[22],"we":[23],"present":[24,131],"Glance,":[25],"a":[26,70,86,163,203],"tool":[27],"that":[28,43,98],"allows":[29],"rapidly":[32],"query,":[33],"sample,":[34],"analyze":[36],"large":[37],"datasets":[39],"for":[40,127,136,153,214],"behavioral":[41],"events":[42,148],"are":[44],"hard":[45],"detect":[47],"automatically.":[48],"Glance":[49,77,99],"takes":[50],"advantage":[51],"the":[53,74,139,145,155,169,187],"parallelism":[54],"available":[55],"in":[56,69,107,123,149,160,186,196],"paid":[57],"online":[58],"crowds":[59],"interpret":[61],"natural":[62,177],"language":[63,178],"queries":[64,198],"then":[66],"aggregates":[67],"responses":[68,82,175],"summary":[71],"view":[72],"data.":[76,218],"provides":[78],"analysts":[79,122],"with":[80,206],"rapid":[81,174],"when":[83,91],"initially":[84],"exploring":[85,216],"dataset,":[87],"reliable":[89],"codings":[90],"refining":[92],"an":[93],"analysis.":[94],"Our":[95],"experiments":[96],"show":[97],"can":[100,117],"code":[101],"nearly":[102],"50":[103],"minutes":[104,109],"5":[108],"by":[110,167],"recruiting":[111],"over":[112],"60":[113],"workers":[114,143],"simultaneously,":[115],"get":[118],"initial":[119],"feedback":[120,180],"under":[124],"10":[125],"seconds":[126],"most":[128],"clips.":[129],"We":[130],"compare":[133],"new":[134,212],"methods":[135],"accurately":[137],"aggregating":[138],"input":[140],"multiple":[142],"marking":[144],"spans":[146],"data,":[151,188],"measuring":[154,168],"quality":[156],"their":[158,207],"real-time":[161],"before":[162],"baseline":[164],"is":[165],"established":[166],"variance":[170],"between":[171],"workers.":[172],"Glance's":[173],"queries,":[179],"regarding":[181],"question":[182],"ambiguity":[183],"anomalies":[185],"ability":[190],"build":[192],"on":[193],"prior":[194],"context":[195],"followup":[197],"allow":[199],"users":[200],"have":[202],"conversation-like":[204],"interaction":[205],"-":[209],"opening":[210],"up":[211],"possibilities":[213],"naturally":[215]},"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":7},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":11},{"year":2018,"cited_by_count":11},{"year":2017,"cited_by_count":11},{"year":2016,"cited_by_count":9},{"year":2015,"cited_by_count":12},{"year":2014,"cited_by_count":4}],"updated_date":"2026-03-27T14:29:43.386196","created_date":"2016-06-24T00:00:00"}