{"id":"https://openalex.org/W4291961169","doi":"https://doi.org/10.1145/3526113.3545681","title":"Scholastic: Graphical Human-AI Collaboration for Inductive and Interpretive Text Analysis","display_name":"Scholastic: Graphical Human-AI Collaboration for Inductive and Interpretive Text Analysis","publication_year":2022,"publication_date":"2022-10-28","ids":{"openalex":"https://openalex.org/W4291961169","doi":"https://doi.org/10.1145/3526113.3545681"},"language":"en","primary_location":{"id":"doi:10.1145/3526113.3545681","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3526113.3545681","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3526113.3545681","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3526113.3545681","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5046026271","display_name":"Matt-Heun Hong","orcid":"https://orcid.org/0000-0003-3169-9654"},"institutions":[{"id":"https://openalex.org/I188538660","display_name":"University of Colorado Boulder","ror":"https://ror.org/02ttsq026","country_code":"US","type":"education","lineage":["https://openalex.org/I188538660"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Matt-Heun Hong","raw_affiliation_strings":["ATLAS Institute, University of Colorado Boulder, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ATLAS Institute, University of Colorado Boulder, United States","institution_ids":["https://openalex.org/I188538660"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104085707","display_name":"Lauren A. Marsh","orcid":null},"institutions":[{"id":"https://openalex.org/I188538660","display_name":"University of Colorado Boulder","ror":"https://ror.org/02ttsq026","country_code":"US","type":"education","lineage":["https://openalex.org/I188538660"]},{"id":"https://openalex.org/I4210131439","display_name":"Applied Mathematics (United States)","ror":"https://ror.org/03seew607","country_code":"US","type":"company","lineage":["https://openalex.org/I4210131439"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lauren A. Marsh","raw_affiliation_strings":["Applied Mathematics, University of Colorado Boulder, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Applied Mathematics, University of Colorado Boulder, United States","institution_ids":["https://openalex.org/I4210131439","https://openalex.org/I188538660"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011438930","display_name":"Jessica L. Feuston","orcid":"https://orcid.org/0000-0002-4049-3589"},"institutions":[{"id":"https://openalex.org/I188538660","display_name":"University of Colorado Boulder","ror":"https://ror.org/02ttsq026","country_code":"US","type":"education","lineage":["https://openalex.org/I188538660"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jessica L. Feuston","raw_affiliation_strings":["Information Science, University of Colorado Boulder, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Science, University of Colorado Boulder, United States","institution_ids":["https://openalex.org/I188538660"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048994200","display_name":"Janet Ruppert","orcid":"https://orcid.org/0000-0002-1216-3515"},"institutions":[{"id":"https://openalex.org/I188538660","display_name":"University of Colorado Boulder","ror":"https://ror.org/02ttsq026","country_code":"US","type":"education","lineage":["https://openalex.org/I188538660"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Janet Ruppert","raw_affiliation_strings":["Information Science, University of Colorado Boulder, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Science, University of Colorado Boulder, United States","institution_ids":["https://openalex.org/I188538660"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084740625","display_name":"Jed R. Brubaker","orcid":"https://orcid.org/0000-0003-4826-8324"},"institutions":[{"id":"https://openalex.org/I188538660","display_name":"University of Colorado Boulder","ror":"https://ror.org/02ttsq026","country_code":"US","type":"education","lineage":["https://openalex.org/I188538660"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jed R. Brubaker","raw_affiliation_strings":["Information Science, University of Colorado Boulder, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Science, University of Colorado Boulder, United States","institution_ids":["https://openalex.org/I188538660"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056903170","display_name":"Danielle Albers Szafir","orcid":"https://orcid.org/0000-0003-3634-8597"},"institutions":[{"id":"https://openalex.org/I114027177","display_name":"University of North Carolina at Chapel Hill","ror":"https://ror.org/0130frc33","country_code":"US","type":"education","lineage":["https://openalex.org/I114027177"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Danielle Albers Szafir","raw_affiliation_strings":["Computer Science, University of North Carolina at Chapel Hill, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science, University of North Carolina at Chapel Hill, United States","institution_ids":["https://openalex.org/I114027177"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":20.5938,"has_fulltext":true,"cited_by_count":26,"citation_normalized_percentile":{"value":0.99218562,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13910","display_name":"Computational and Text Analysis Methods","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/3300","display_name":"General Social Sciences"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T13910","display_name":"Computational and Text Analysis Methods","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/3300","display_name":"General Social Sciences"},"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/T13398","display_name":"Data Analysis with R","score":0.9876000285148621,"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/T10799","display_name":"Data Visualization and Analytics","score":0.9786999821662903,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7957983613014221},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6421471834182739},{"id":"https://openalex.org/keywords/metadata","display_name":"Metadata","score":0.6214134693145752},{"id":"https://openalex.org/keywords/document-clustering","display_name":"Document clustering","score":0.5350324511528015},{"id":"https://openalex.org/keywords/schema","display_name":"Schema (genetic algorithms)","score":0.5325364470481873},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.456635981798172},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.45341619849205017},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.44815242290496826},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4464796483516693},{"id":"https://openalex.org/keywords/hierarchical-clustering","display_name":"Hierarchical clustering","score":0.4460238516330719},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.41131591796875},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.23330745100975037}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7957983613014221},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6421471834182739},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.6214134693145752},{"id":"https://openalex.org/C177937566","wikidata":"https://www.wikidata.org/wiki/Q4223102","display_name":"Document clustering","level":3,"score":0.5350324511528015},{"id":"https://openalex.org/C52146309","wikidata":"https://www.wikidata.org/wiki/Q7431116","display_name":"Schema (genetic algorithms)","level":2,"score":0.5325364470481873},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.456635981798172},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.45341619849205017},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.44815242290496826},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4464796483516693},{"id":"https://openalex.org/C92835128","wikidata":"https://www.wikidata.org/wiki/Q1277447","display_name":"Hierarchical clustering","level":3,"score":0.4460238516330719},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.41131591796875},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.23330745100975037},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"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":2,"locations":[{"id":"doi:10.1145/3526113.3545681","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3526113.3545681","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3526113.3545681","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2208.06133","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2208.06133","pdf_url":"https://arxiv.org/pdf/2208.06133","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":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1145/3526113.3545681","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3526113.3545681","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3526113.3545681","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.5799999833106995}],"awards":[{"id":"https://openalex.org/G1391282728","display_name":"CHS: Medium: Scaling Qualitative Inductive Analysis through Computational Methods","funder_award_id":"1764089","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G1915859349","display_name":"CHS: Medium: Data-Mediated Communication with Proximal Robots for Emergency Response","funder_award_id":"1764092","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5792890549","display_name":"CAREER: HCC: Developing Perceptually-Driven Tools for Estimating Visualization Effectiveness","funder_award_id":"2046725","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"},{"id":"https://openalex.org/F4320332538","display_name":"University of Colorado Boulder","ror":"https://ror.org/02ttsq026"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4291961169.pdf","grobid_xml":"https://content.openalex.org/works/W4291961169.grobid-xml"},"referenced_works_count":50,"referenced_works":["https://openalex.org/W184934546","https://openalex.org/W377384883","https://openalex.org/W976506165","https://openalex.org/W1536494821","https://openalex.org/W1607675442","https://openalex.org/W1826129262","https://openalex.org/W1979290264","https://openalex.org/W1991676464","https://openalex.org/W1993503217","https://openalex.org/W2027855569","https://openalex.org/W2072403461","https://openalex.org/W2081459780","https://openalex.org/W2087382273","https://openalex.org/W2090491854","https://openalex.org/W2095655043","https://openalex.org/W2102907934","https://openalex.org/W2112971401","https://openalex.org/W2117667023","https://openalex.org/W2217516311","https://openalex.org/W2250239827","https://openalex.org/W2535633424","https://openalex.org/W2546996098","https://openalex.org/W2595494611","https://openalex.org/W2607618454","https://openalex.org/W2733660482","https://openalex.org/W2738411409","https://openalex.org/W2742276251","https://openalex.org/W2756188544","https://openalex.org/W2769563773","https://openalex.org/W2809100814","https://openalex.org/W2901481055","https://openalex.org/W2964291985","https://openalex.org/W2965022010","https://openalex.org/W2969954596","https://openalex.org/W2979893369","https://openalex.org/W3011600893","https://openalex.org/W3017863658","https://openalex.org/W3019215050","https://openalex.org/W3037826211","https://openalex.org/W3104490701","https://openalex.org/W3124673268","https://openalex.org/W3174776221","https://openalex.org/W3207098447","https://openalex.org/W3215074405","https://openalex.org/W4226093430","https://openalex.org/W4231510805","https://openalex.org/W4285791162","https://openalex.org/W4288076015","https://openalex.org/W4288410082","https://openalex.org/W4301230818"],"related_works":["https://openalex.org/W2058118494","https://openalex.org/W2392768766","https://openalex.org/W2382021449","https://openalex.org/W2095118173","https://openalex.org/W4237492828","https://openalex.org/W78181647","https://openalex.org/W2130194910","https://openalex.org/W2189374779","https://openalex.org/W2605148547","https://openalex.org/W2016788389"],"abstract_inverted_index":{"Interpretive":[0],"scholars":[1,118],"generate":[2],"knowledge":[3],"from":[4,108],"text":[5,80],"corpora":[6],"by":[7],"manually":[8],"sampling":[9,35],"documents,":[10],"applying":[11],"codes,":[12],"and":[13,15,36,89,104,131,139,147],"refining":[14],"collating":[16],"codes":[17,86],"into":[18],"categories":[19],"until":[20],"meaningful":[21],"themes":[22],"emerge.":[23],"Given":[24],"a":[25,57,73,83],"large":[26],"corpus,":[27],"machine":[28],"learning":[29],"could":[30],"help":[31,117],"scale":[32],"this":[33],"data":[34],"analysis,":[37],"but":[38],"prior":[39],"research":[40,67,141],"shows":[41],"that":[42],"experts":[43],"are":[44],"generally":[45],"concerned":[46],"about":[47],"algorithms":[48],"potentially":[49],"disrupting":[50],"or":[51],"driving":[52],"interpretive":[53,66,79,140],"scholarship.":[54],"We":[55],"take":[56],"human-centered":[58,128],"design":[59,130],"approach":[60],"to":[61,68,77,87],"addressing":[62],"concerns":[63],"around":[64],"machine-assisted":[65],"build":[69],"Scholastic,":[70],"which":[71,100],"incorporates":[72],"machine-in-the-loop":[74],"clustering":[75],"algorithm":[76,129],"scaffold":[78],"analysis.":[81],"As":[82],"scholar":[84],"applies":[85],"documents":[88,121],"refines":[90],"them,":[91],"the":[92,109],"resulting":[93],"coding":[94],"schema":[95],"serves":[96],"as":[97],"structured":[98],"metadata":[99],"constrains":[101],"hierarchical":[102],"document":[103,148],"word":[105],"clusters":[106,115],"inferred":[107],"corpus.":[110],"Interactive":[111],"visualizations":[112,132],"of":[113],"these":[114],"can":[116,136],"strategically":[119],"sample":[120],"further":[122],"toward":[123],"insights.":[124],"Scholastic":[125],"demonstrates":[126],"how":[127],"employing":[133],"familiar":[134],"metaphors":[135],"support":[137],"inductive":[138],"methodologies":[142],"through":[143],"interactive":[144],"topic":[145],"modeling":[146],"clustering.":[149]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":4}],"updated_date":"2026-07-03T08:13:44.112507","created_date":"2022-08-16T00:00:00"}
