{"id":"https://openalex.org/W2528309064","doi":"https://doi.org/10.1109/edocw.2016.7584388","title":"Social Set Visualizer (SoSeVi) II: Interactive Computational Set Analysis of Big Social Data","display_name":"Social Set Visualizer (SoSeVi) II: Interactive Computational Set Analysis of Big Social Data","publication_year":2016,"publication_date":"2016-09-01","ids":{"openalex":"https://openalex.org/W2528309064","doi":"https://doi.org/10.1109/edocw.2016.7584388","mag":"2528309064"},"language":"en","primary_location":{"id":"doi:10.1109/edocw.2016.7584388","is_oa":false,"landing_page_url":"https://doi.org/10.1109/edocw.2016.7584388","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 20th International Enterprise Distributed Object Computing Workshop (EDOCW)","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/A5019393777","display_name":"Benjamin Flesch","orcid":null},"institutions":[{"id":"https://openalex.org/I180519160","display_name":"Copenhagen Business School","ror":"https://ror.org/04sppb023","country_code":"DK","type":"education","lineage":["https://openalex.org/I180519160"]}],"countries":["DK"],"is_corresponding":true,"raw_author_name":"Benjamin Flesch","raw_affiliation_strings":["Copenhagen Business School, Denmark"],"affiliations":[{"raw_affiliation_string":"Copenhagen Business School, Denmark","institution_ids":["https://openalex.org/I180519160"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074288048","display_name":"Ravi Vatrapu","orcid":"https://orcid.org/0000-0002-9109-5281"},"institutions":[{"id":"https://openalex.org/I2801609477","display_name":"Westerdals Oslo School of Arts, Communication and Technology","ror":"https://ror.org/02re25503","country_code":"NO","type":"education","lineage":["https://openalex.org/I2801609477"]},{"id":"https://openalex.org/I180519160","display_name":"Copenhagen Business School","ror":"https://ror.org/04sppb023","country_code":"DK","type":"education","lineage":["https://openalex.org/I180519160"]}],"countries":["DK","NO"],"is_corresponding":false,"raw_author_name":"Ravi Vatrapu","raw_affiliation_strings":["Copenhagen Business School, Denmark","Westerdals Oslo School of Arts, Comm & Tech, Norway"],"affiliations":[{"raw_affiliation_string":"Copenhagen Business School, Denmark","institution_ids":["https://openalex.org/I180519160"]},{"raw_affiliation_string":"Westerdals Oslo School of Arts, Comm & Tech, Norway","institution_ids":["https://openalex.org/I2801609477"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5019393777"],"corresponding_institution_ids":["https://openalex.org/I180519160"],"apc_list":null,"apc_paid":null,"fwci":0.221,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.59495768,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.998199999332428,"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":0.998199999332428,"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/T10799","display_name":"Data Visualization and Analytics","score":0.9937999844551086,"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/T13283","display_name":"Mental Health Research Topics","score":0.9732000231742859,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7717440128326416},{"id":"https://openalex.org/keywords/cultural-analytics","display_name":"Cultural analytics","score":0.7503516674041748},{"id":"https://openalex.org/keywords/visual-analytics","display_name":"Visual analytics","score":0.7405162453651428},{"id":"https://openalex.org/keywords/interactive-visual-analysis","display_name":"Interactive visual analysis","score":0.7392538785934448},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.6943559050559998},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6619738340377808},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.6491436958312988},{"id":"https://openalex.org/keywords/dashboard","display_name":"Dashboard","score":0.6356201171875},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.5965685844421387},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.5452260971069336},{"id":"https://openalex.org/keywords/data-visualization","display_name":"Data visualization","score":0.5206714868545532},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.35454368591308594},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.3422548174858093},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.22874432802200317},{"id":"https://openalex.org/keywords/semantic-analytics","display_name":"Semantic analytics","score":0.20003476738929749},{"id":"https://openalex.org/keywords/social-semantic-web","display_name":"Social Semantic Web","score":0.13954880833625793},{"id":"https://openalex.org/keywords/semantic-web","display_name":"Semantic Web","score":0.11531388759613037}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7717440128326416},{"id":"https://openalex.org/C545860419","wikidata":"https://www.wikidata.org/wiki/Q5193251","display_name":"Cultural analytics","level":5,"score":0.7503516674041748},{"id":"https://openalex.org/C59732488","wikidata":"https://www.wikidata.org/wiki/Q2528440","display_name":"Visual analytics","level":3,"score":0.7405162453651428},{"id":"https://openalex.org/C99740376","wikidata":"https://www.wikidata.org/wiki/Q17092520","display_name":"Interactive visual analysis","level":4,"score":0.7392538785934448},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.6943559050559998},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6619738340377808},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.6491436958312988},{"id":"https://openalex.org/C33499554","wikidata":"https://www.wikidata.org/wiki/Q1417134","display_name":"Dashboard","level":2,"score":0.6356201171875},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.5965685844421387},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.5452260971069336},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.5206714868545532},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.35454368591308594},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.3422548174858093},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.22874432802200317},{"id":"https://openalex.org/C148792806","wikidata":"https://www.wikidata.org/wiki/Q7449046","display_name":"Semantic analytics","level":4,"score":0.20003476738929749},{"id":"https://openalex.org/C534406577","wikidata":"https://www.wikidata.org/wiki/Q7550843","display_name":"Social Semantic Web","level":3,"score":0.13954880833625793},{"id":"https://openalex.org/C2129575","wikidata":"https://www.wikidata.org/wiki/Q54837","display_name":"Semantic Web","level":2,"score":0.11531388759613037},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/edocw.2016.7584388","is_oa":false,"landing_page_url":"https://doi.org/10.1109/edocw.2016.7584388","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 20th International Enterprise Distributed Object Computing Workshop (EDOCW)","raw_type":"proceedings-article"},{"id":"pmh:oai:research-api.cbs.dk:openaire_cris_publications/0502939b-d71e-44ed-9c49-85be09e029d2","is_oa":false,"landing_page_url":"https://research.cbs.dk/en/publications/0502939b-d71e-44ed-9c49-85be09e029d2","pdf_url":null,"source":{"id":"https://openalex.org/S4306401458","display_name":"CBS Research Portal (Copenhagen Business School)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I180519160","host_organization_name":"Copenhagen Business School","host_organization_lineage":["https://openalex.org/I180519160"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Flesch, B & Vatrapu, R 2016, Social Set Visualizer (SoSeVi) II : Interactive Computational Set Analysis of Big Social Data. in S Rinderle-Ma, L F Pires & R Dijkman (eds), 2016 IEEE 20th International Enterprise Distributed Object Computing Workshop (EDOCW 2016)., 7584388, IEEE, Los Alamitos, CA, Proceedings of the Enterprise Distributed Object Computing Conference Workshops. EDOCW, vol. 2016, pp. 332-335, The 20th IEEE International Enterprise Distributed Object Computing. EDOC 2016, Vienna , Austria, 05/09/2016. https://doi.org/10.1109/EDOCW.2016.7584388","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8199999928474426,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320330516","display_name":"Industriens Fond","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W9225096","https://openalex.org/W1791522095","https://openalex.org/W1915688508","https://openalex.org/W1973012451","https://openalex.org/W1991189300","https://openalex.org/W2049427312","https://openalex.org/W2066778800","https://openalex.org/W2085341005","https://openalex.org/W2130162792","https://openalex.org/W2199825281","https://openalex.org/W2342845725","https://openalex.org/W2465545188","https://openalex.org/W6679109501"],"related_works":["https://openalex.org/W2148525144","https://openalex.org/W1813318416","https://openalex.org/W3173715284","https://openalex.org/W2564956852","https://openalex.org/W2158984754","https://openalex.org/W3149127250","https://openalex.org/W4246764483","https://openalex.org/W3208630418","https://openalex.org/W4409660181","https://openalex.org/W2112083262"],"abstract_inverted_index":{"This":[0],"paper":[1],"reports":[2],"the":[3,7,44,48,67],"second":[4],"iteration":[5,46],"of":[6,18,34,39,47,66,80,85,100],"Social":[8,49],"Set":[9,50],"Visualizer":[10,51],"(SoSeVi),":[11],"a":[12],"set":[13,62],"theoretical":[14],"visual":[15,31,74],"analytics":[16,32,75],"dashboard":[17,69],"big":[19],"social":[20,42,105],"data.":[21],"In":[22],"order":[23],"to":[24],"further":[25],"demonstrate":[26],"its":[27],"usefulness":[28],"in":[29,41,53,60],"large-scale":[30],"tasks":[33],"individual":[35],"and":[36,78,90,94],"collective":[37],"behavior":[38],"actors":[40],"networks,":[43],"current":[45],"(SoSeVi)":[52],"version":[54],"II":[55,97],"builds":[56],"on":[57],"recent":[58],"advancements":[59],"visualizing":[61],"intersections.":[63],"The":[64],"development":[65],"SoSeVi":[68,96],"involved":[70],"cutting-edge":[71],"open":[72],"source":[73],"libraries":[76],"(D3.js)":[77],"creation":[79],"new":[81],"visualizations":[82],"such":[83],"as":[84],"actor":[86],"mobility":[87],"across":[88],"time":[89],"space,":[91],"conversational":[92],"comets,":[93],"more.":[95],"introduces":[98],"means":[99],"real-time":[101],"migration":[102],"visualization":[103],"between":[104],"sets.":[106]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
