Literature DB >> 17073366

Visual analysis of large heterogeneous social networks by semantic and structural abstraction.

Zeqian Shen1, Kwan-Liu Ma, Tina Eliassi-Rad.   

Abstract

Social network analysis is an active area of study beyond sociology. It uncovers the invisible relationships between actors in a network and provides understanding of social processes and behaviors. It has become an important technique in a variety of application areas such as the Web, organizational studies, and homeland security. This paper presents a visual analytics tool, OntoVis, for understanding large, heterogeneous social networks, in which nodes and links could represent different concepts and relations, respectively. These concepts and relations are related through an ontology (also known as a schema). OntoVis is named such because it uses information in the ontology associated with a social network to semantically prune a large, heterogeneous network. In addition to semantic abstraction, OntoVis also allows users to do structural abstraction and importance filtering to make large networks manageable and to facilitate analytic reasoning. All these unique capabilities of OntoVis are illustrated with several case studies.

Mesh:

Year:  2006        PMID: 17073366     DOI: 10.1109/TVCG.2006.107

Source DB:  PubMed          Journal:  IEEE Trans Vis Comput Graph        ISSN: 1077-2626            Impact factor:   4.579


  6 in total

1.  TS-Extractor: large graph exploration via subgraph extraction based on topological and semantic information.

Authors:  Kun Fu; Tingyun Mao; Yang Wang; Daoyu Lin; Yuanben Zhang; Junjian Zhan; Xian Sun; Feng Li
Journal:  J Vis (Tokyo)       Date:  2020-09-22       Impact factor: 1.331

2.  Similar but Different: Dynamic Social Network Analysis Highlights Fundamental Differences between the Fission-Fusion Societies of Two Equid Species, the Onager and Grevy's Zebra.

Authors:  Daniel I Rubenstein; Siva R Sundaresan; Ilya R Fischhoff; Chayant Tantipathananandh; Tanya Y Berger-Wolf
Journal:  PLoS One       Date:  2015-10-21       Impact factor: 3.240

3.  Summarizing Complex Graphical Models of Multiple Chronic Conditions Using the Second Eigenvalue of Graph Laplacian: Algorithm Development and Validation.

Authors:  Adel Alaeddini; Syed Hasib Akhter Faruqui; Mike C Chang; Sara Shirinkam; Carlos Jaramillo; Peyman NajafiRad; Jing Wang; Mary Jo Pugh
Journal:  JMIR Med Inform       Date:  2020-06-17

Review 4.  Network science approach to modelling the topology and robustness of supply chain networks: a review and perspective.

Authors:  Supun Perera; Michael G H Bell; Michiel C J Bliemer
Journal:  Appl Netw Sci       Date:  2017-10-10

5.  Ontology-Based Graphs of Research Communities: A Tool for Understanding Threat Reduction Networks.

Authors:  John Ambrosiano; Benjamin Sims; Andrew W Bartlow; William Rosenberger; Mark Ressler; Jeanne M Fair
Journal:  Front Res Metr Anal       Date:  2020-06-09

6.  A survey of Big Data dimensions vs Social Networks analysis.

Authors:  Michele Ianni; Elio Masciari; Giancarlo Sperlí
Journal:  J Intell Inf Syst       Date:  2020-11-09       Impact factor: 1.888

  6 in total

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