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On the use of Multiple Correspondence Analysis to visually explore affiliation networks

Bibliographic Data

ID8017946
AuthorsMaria Rosaria D’esposito (0000-0001-9963-8378, University of Salerno), Domenico De Stefano (0000-0003-1120-2524, Ca' Foscari University of Venice), Giancarlo Ragozini (0000-0002-2385-4645, University of Naples Federico II)
Year2014
Volume38
Pages28-40
Publication date2014-03-10
Open AccessNo
TypeARTICLE
VenueSocial Networks (JOURNAL)
Journal identifiersISSN: 0378-8733 • E-ISSN: 1879-2111
PublisherElsevier BV (PUBLISHER)
DOI10.1016/j.socnet.2014.01.003
OpenAlexW2011634877
LanguageEN
Citations received15
References cited31

Correspondence analysis · Data mining · Epistemology · Human–computer interaction · Interpretation (philosophy · Machine learning · Mode (computer interface · Multiple correspondence analysis · Network analysis · Order (exchange · Perspective (graphical · Simple (philosophy · Complex Network Analysis Techniques · Computer Science · Data Visualization and Analytics · Topological and Geometric Data Analysis · Artificial Intelligence · Theoretical Computer Science

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  • Taste on Facebook

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  • Multiple factor analysis for time-varying two-mode networks

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  • Multiple Correspondence Analysis and Related Methods

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Citations per year1.36
Citation span2015 - 2026 (12)
Highly citedNo

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