Multivariate social network visual analytics

Chris Muelder, Liang Gou, Kwan-Liu Ma, Michelle X. Zhou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

One of the key research topics in Social Science and Sociology is to understand and analyze various social networks. Like any other types of networks, a social network consists of a set of nodes and links. Here, each node often represents a social entity, such as an individual or a group, and each link represents a particular relationship between two social entities. In a multivariate social network, each node/link can be associated with a set of properties, or there can even be multiple sets of heterogenous nodes or edges.

Original languageEnglish (US)
Title of host publicationMultivariate Network Visualization - Dagstuhl Seminar #13201, Revised Discussions
PublisherSpringer-Verlag
Pages37-59
Number of pages23
ISBN (Print)9783319067926
DOIs
StatePublished - Jan 1 2014
Event3rd Dagstuhl Seminar on Information Visualization - Towards Multivariate Network Visualization - Saarland, Germany
Duration: May 12 2013May 17 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8380 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other3rd Dagstuhl Seminar on Information Visualization - Towards Multivariate Network Visualization
CountryGermany
CitySaarland
Period5/12/135/17/13

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint Dive into the research topics of 'Multivariate social network visual analytics'. Together they form a unique fingerprint.

  • Cite this

    Muelder, C., Gou, L., Ma, K-L., & Zhou, M. X. (2014). Multivariate social network visual analytics. In Multivariate Network Visualization - Dagstuhl Seminar #13201, Revised Discussions (pp. 37-59). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8380 LNCS). Springer-Verlag. https://doi.org/10.1007/978-3-319-06793-3_3