{"id":"https://openalex.org/W2289576527","doi":"https://doi.org/10.1145/2856767.2856787","title":"Topic Modeling of Document Metadata for Visualizing Collaborations over Time","display_name":"Topic Modeling of Document Metadata for Visualizing Collaborations over Time","publication_year":2016,"publication_date":"2016-03-03","ids":{"openalex":"https://openalex.org/W2289576527","doi":"https://doi.org/10.1145/2856767.2856787","mag":"2289576527"},"language":"en","primary_location":{"id":"doi:10.1145/2856767.2856787","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2856767.2856787","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 21st International Conference on Intelligent User Interfaces","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/A5025376488","display_name":"Francine Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I26274970","display_name":"FX Palo Alto Laboratory","ror":"https://ror.org/05ef4zt88","country_code":"US","type":"facility","lineage":["https://openalex.org/I26274970"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Francine Chen","raw_affiliation_strings":["FX Palo Alto Laboratory, Palo Alto, CA, USA"],"affiliations":[{"raw_affiliation_string":"FX Palo Alto Laboratory, Palo Alto, CA, USA","institution_ids":["https://openalex.org/I26274970"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103331862","display_name":"Patrick Chiu","orcid":null},"institutions":[{"id":"https://openalex.org/I26274970","display_name":"FX Palo Alto Laboratory","ror":"https://ror.org/05ef4zt88","country_code":"US","type":"facility","lineage":["https://openalex.org/I26274970"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Patrick Chiu","raw_affiliation_strings":["FX Palo Alto Laboratory, Palo Alto, CA, USA"],"affiliations":[{"raw_affiliation_string":"FX Palo Alto Laboratory, Palo Alto, CA, USA","institution_ids":["https://openalex.org/I26274970"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069628653","display_name":"Seongtaek Lim","orcid":null},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Seongtaek Lim","raw_affiliation_strings":["University of California, Berkeley, Berkeley, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of California, Berkeley, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5025376488"],"corresponding_institution_ids":["https://openalex.org/I26274970"],"apc_list":null,"apc_paid":null,"fwci":1.5469,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.83019121,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"108","last_page":"117"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9980999827384949,"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":0.9955999851226807,"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/latent-dirichlet-allocation","display_name":"Latent Dirichlet allocation","score":0.8955918550491333},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8407727479934692},{"id":"https://openalex.org/keywords/metadata","display_name":"Metadata","score":0.7685174942016602},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.6438300609588623},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5709699392318726},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.5642942786216736},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4676035940647125},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.45172351598739624},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.44968196749687195},{"id":"https://openalex.org/keywords/multidimensional-scaling","display_name":"Multidimensional scaling","score":0.4426499009132385},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.43078354001045227},{"id":"https://openalex.org/keywords/metadata-modeling","display_name":"Metadata modeling","score":0.4193165600299835},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.34711599349975586},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.33063751459121704},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.297254353761673},{"id":"https://openalex.org/keywords/metadata-repository","display_name":"Metadata repository","score":0.14551737904548645},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.11926871538162231},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1076100766658783},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.09865695238113403},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.09604096412658691}],"concepts":[{"id":"https://openalex.org/C500882744","wikidata":"https://www.wikidata.org/wiki/Q269236","display_name":"Latent Dirichlet allocation","level":3,"score":0.8955918550491333},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8407727479934692},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.7685174942016602},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.6438300609588623},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5709699392318726},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.5642942786216736},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4676035940647125},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.45172351598739624},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.44968196749687195},{"id":"https://openalex.org/C91682802","wikidata":"https://www.wikidata.org/wiki/Q620538","display_name":"Multidimensional scaling","level":2,"score":0.4426499009132385},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.43078354001045227},{"id":"https://openalex.org/C110326360","wikidata":"https://www.wikidata.org/wiki/Q17149476","display_name":"Metadata modeling","level":4,"score":0.4193165600299835},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.34711599349975586},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.33063751459121704},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.297254353761673},{"id":"https://openalex.org/C153048206","wikidata":"https://www.wikidata.org/wiki/Q3454922","display_name":"Metadata repository","level":3,"score":0.14551737904548645},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.11926871538162231},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1076100766658783},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.09865695238113403},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.09604096412658691},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","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/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2856767.2856787","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2856767.2856787","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 21st International Conference on Intelligent User Interfaces","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4300000071525574,"id":"https://metadata.un.org/sdg/17","display_name":"Partnerships for the goals"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1548468326","https://openalex.org/W1550037799","https://openalex.org/W1605767199","https://openalex.org/W1831355885","https://openalex.org/W1880262756","https://openalex.org/W1993916866","https://openalex.org/W2017447209","https://openalex.org/W2026302857","https://openalex.org/W2057444996","https://openalex.org/W2090491854","https://openalex.org/W2111708605","https://openalex.org/W2122843645","https://openalex.org/W2130339025","https://openalex.org/W2142071678","https://openalex.org/W2151575822","https://openalex.org/W2153579005","https://openalex.org/W2154562480","https://openalex.org/W2167704725"],"related_works":["https://openalex.org/W2769501189","https://openalex.org/W4315588616","https://openalex.org/W4312773271","https://openalex.org/W2888805565","https://openalex.org/W2962686197","https://openalex.org/W2207653751","https://openalex.org/W3159709618","https://openalex.org/W2611137333","https://openalex.org/W3005513013","https://openalex.org/W4389543811"],"abstract_inverted_index":{"We":[0,16,96,147],"describe":[1],"methods":[2],"for":[3,104,174],"analyzing":[4],"and":[5,57,91,120,141,157,170],"visualizing":[6],"document":[7],"metadata":[8,160],"to":[9,28,69,72,154],"provide":[10],"insights":[11],"about":[12],"collaborations":[13],"over":[14,164],"time.":[15],"investigate":[17],"the":[18,58,81,88,98,105,112,116,124,142,149],"use":[19],"of":[20,31,100,167],"Latent":[21],"Dirichlet":[22],"Allocation":[23],"(LDA)":[24],"based":[25],"topic":[26,102,109,138],"modeling":[27,103],"compute":[29],"areas":[30],"interest":[32],"on":[33],"which":[34],"people":[35,59,89],"collaborate.":[36],"The":[37,64],"topics":[38,65,75],"are":[39,66,93],"represented":[40],"in":[41,133,144],"a":[42,77,84,137,145,165],"node-link":[43],"force":[44],"directed":[45],"graph":[46],"by":[47,60,107,128],"persistent":[48],"fixed":[49],"nodes":[50,90],"laid":[51],"out":[52],"with":[53],"multidimensional":[54],"scaling":[55],"(MDS),":[56],"transient":[61],"movable":[62],"nodes.":[63],"also":[67],"analyzed":[68],"detect":[70],"bursts":[71],"highlight":[73],"\"hot\"":[74],"during":[76],"time":[78,85],"interval.":[79],"As":[80],"user":[82],"manipulates":[83],"interval":[86],"slider,":[87],"links":[92],"dynamically":[94],"updated.":[95],"evaluate":[97],"results":[99],"LDA":[101],"visualization":[106],"comparing":[108],"keywords":[110,114],"against":[111],"submitted":[113],"from":[115,152,161],"InfoVis":[117,150],"2004":[118],"Contest,":[119],"we":[121],"found":[122],"that":[123],"additional":[125],"terms":[126],"provided":[127],"LDA-based":[129],"keyword":[130,139],"sets":[131],"result":[132],"improved":[134],"similarity":[135],"between":[136],"set":[140],"documents":[143],"corpus.":[146],"extended":[148],"dataset":[151],"8":[153],"20":[155],"years":[156],"collected":[158],"publication":[159],"our":[162],"lab":[163],"period":[166],"21":[168],"years,":[169],"created":[171],"interactive":[172],"visualizations":[173],"exploring":[175],"these":[176],"larger":[177],"datasets.":[178]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}