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Cited by 193

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Visual Analysis of Large Heterogeneous Social Networks by Semantic and Structural Abstraction

Zeqian Shen, Kwan-Liu Ma, Eliassi-Rad, T.·2006·IEEE Transactions on Visualization and Computer Graphics

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.

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Metadata

Authors
Shen, Z., Ma, K.-L., & Eliassi-Rad, T.
Venue
IEEE Transactions on Visualization and Computer Graphics
Published
2006-11
Volume
12
Issue
6
Pages
1427-1439
ISSN
  • 1077-2626 (ISSN-L)
  • 1941-0506
  • 2160-9306
OpenAlex
W2137161844
Cited by
193
References
1
FWCI
10.19
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Visual Analysis of Large Heterogeneous Social Networks by Semantic and Structural Abstraction. https://app.cochat.ai/papers/10.1109/tvcg.2006.107
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Shen, Z., Ma, K.-L., & Eliassi-Rad, T. (2006). Visual Analysis of Large Heterogeneous Social Networks by Semantic and Structural Abstraction. IEEE Transactions on Visualization and Computer Graphics. https://doi.org/10.1109/tvcg.2006.107

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