{"id":"https://openalex.org/W2099147981","doi":"https://doi.org/10.1145/2470654.2481373","title":"Quantity estimation in visualizations of tagged text","display_name":"Quantity estimation in visualizations of tagged text","publication_year":2013,"publication_date":"2013-04-27","ids":{"openalex":"https://openalex.org/W2099147981","doi":"https://doi.org/10.1145/2470654.2481373","mag":"2099147981"},"language":"en","primary_location":{"id":"doi:10.1145/2470654.2481373","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2470654.2481373","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the SIGCHI Conference on Human Factors in Computing Systems","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/A5036300289","display_name":"Michael Correll","orcid":"https://orcid.org/0000-0001-7902-3907"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Michael A. Correll","raw_affiliation_strings":["University of Wisconsin - Madison, Madison, Wisconsin, USA"],"affiliations":[{"raw_affiliation_string":"University of Wisconsin - Madison, Madison, Wisconsin, USA","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087042012","display_name":"Eric Alexander","orcid":"https://orcid.org/0000-0002-6984-7360"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Eric C. Alexander","raw_affiliation_strings":["University of Wisconsin - Madison, Madison, Wisconsin, USA"],"affiliations":[{"raw_affiliation_string":"University of Wisconsin - Madison, Madison, Wisconsin, USA","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084778474","display_name":"Michael Gleicher","orcid":"https://orcid.org/0000-0003-3295-4071"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael Gleicher","raw_affiliation_strings":["University of Wisconsin - Madison, Madison, Wisconsin, USA"],"affiliations":[{"raw_affiliation_string":"University of Wisconsin - Madison, Madison, Wisconsin, USA","institution_ids":["https://openalex.org/I135310074"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5036300289"],"corresponding_institution_ids":["https://openalex.org/I135310074"],"apc_list":null,"apc_paid":null,"fwci":2.2115,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.89775634,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"2697","last_page":"2706"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10799","display_name":"Data Visualization and Analytics","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10799","display_name":"Data Visualization and Analytics","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11439","display_name":"Video Analysis and Summarization","score":0.9908999800682068,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9692999720573425,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8209441900253296},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6785045862197876},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6630615592002869},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.6178598999977112},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5848339796066284},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5390381813049316},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.5000932216644287},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45739516615867615},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.40091633796691895}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8209441900253296},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6785045862197876},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6630615592002869},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.6178598999977112},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5848339796066284},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5390381813049316},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5000932216644287},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45739516615867615},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.40091633796691895},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"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/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","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},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2470654.2481373","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2470654.2481373","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the SIGCHI Conference on Human Factors in Computing Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.430.9352","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.430.9352","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"https://graphics.cs.wisc.edu/Papers/2013/CAG13/chi2013.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.7699999809265137}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320306146","display_name":"Andrew W. Mellon Foundation","ror":"https://ror.org/04jsh2530"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337391","display_name":"Division of Civil, Mechanical and Manufacturing Innovation","ror":"https://ror.org/028yd4c30"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1814571536","https://openalex.org/W1983726079","https://openalex.org/W1997290056","https://openalex.org/W2001274155","https://openalex.org/W2005111635","https://openalex.org/W2011504960","https://openalex.org/W2018041479","https://openalex.org/W2025861473","https://openalex.org/W2035707873","https://openalex.org/W2041232552","https://openalex.org/W2043372954","https://openalex.org/W2049338438","https://openalex.org/W2052021538","https://openalex.org/W2066276892","https://openalex.org/W2075038621","https://openalex.org/W2078519269","https://openalex.org/W2085848071","https://openalex.org/W2092614576","https://openalex.org/W2102269059","https://openalex.org/W2110890346","https://openalex.org/W2114269021","https://openalex.org/W2114566476","https://openalex.org/W2120357670","https://openalex.org/W2121517332","https://openalex.org/W2139437238","https://openalex.org/W2141233457","https://openalex.org/W2151401338","https://openalex.org/W2184024011","https://openalex.org/W2322839822","https://openalex.org/W2333080640","https://openalex.org/W3123895079","https://openalex.org/W3148487900","https://openalex.org/W4243242078","https://openalex.org/W4256583779","https://openalex.org/W4285719527","https://openalex.org/W6649488820","https://openalex.org/W6663613830","https://openalex.org/W7029202173"],"related_works":["https://openalex.org/W2357241418","https://openalex.org/W2081647779","https://openalex.org/W2789919619","https://openalex.org/W2086064646","https://openalex.org/W2119135658","https://openalex.org/W2115485936","https://openalex.org/W2363669182","https://openalex.org/W2293457016","https://openalex.org/W2525150146","https://openalex.org/W2512130900"],"abstract_inverted_index":{"A":[0],"valuable":[1],"task":[2],"in":[3,51],"text":[4,13,27,53,55],"visualization":[5],"is":[6],"to":[7,42],"have":[8],"viewers":[9,41,84],"make":[10,43],"judgments":[11,44],"about":[12,45],"that":[14,70,83],"has":[15],"been":[16],"annotated":[17,52],"(either":[18],"by":[19,22],"hand":[20],"or":[21,29],"some":[23],"algorithm":[24],"such":[25],"as":[26],"clustering":[28],"entity":[30],"extraction).":[31],"In":[32],"this":[33],"work":[34],"we":[35],"look":[36],"at":[37,74],"the":[38,46,90],"ability":[39],"of":[40,49,59,62,92,98],"relative":[47],"quantities":[48],"tags":[50],"(specifically":[54],"tagged":[56],"with":[57],"one":[58],"a":[60,96],"set":[61],"qualitatively":[63],"distinct":[64],"colors),":[65],"and":[66,87,108],"examine":[67],"design":[68],"choices":[69],"can":[71,85,102],"improve":[72],"performance":[73],"extracting":[75],"statistical":[76],"information":[77],"from":[78],"these":[79],"texts.":[80],"We":[81],"find":[82],"efficiently":[86],"accurately":[88],"estimate":[89],"proportions":[91],"tag":[93],"levels":[94],"over":[95],"range":[97],"situations;":[99],"however":[100],"accuracy":[101],"be":[103],"improved":[104],"through":[105],"color":[106],"choice":[107],"area":[109],"adjustments.":[110]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":3},{"year":2014,"cited_by_count":4},{"year":2013,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}