From spatial proximity to semantic coherence

A quantitative approach to the study of group dynamics in collaborative virtual environments

Chaomei Chen, Katy Börner

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

This article describes a quantitative approach to the study of group dynamics in Collaborative Information Visualization Environments (CIVEs). This approach characterizes group dynamics in terms of two concepts introduced in this article - spatial proximity and semantic coherence. The concepts are crucial to the understanding of profound interrelationships between spatial, semantic, and social navigation. Further-more, this article describes three visualization techniques - semantic indentation chat sequence displays, activity maps, and clock-face maps - that permit the identification of important features of group interaction that are related to semantic coherence and spatial proximity. The approach is illustrated by applying it to the analysis of an empirical study in which four groups of subjects performed collaborative search tasks through 3D visualizations of knowledge domains. The major contribution of the work is the conceptualization and quantification of group coherence as a generic methodology for the study of a range of collaborative virtual environments such as collaborative learning, distance learning, social networks, collaborative information visualization, and digital libraries. Further research challenges for the study of group behavior in collaborative information-visualization environments are identified.

Original languageEnglish
Pages (from-to)81-103
Number of pages23
JournalPresence: Teleoperators and Virtual Environments
Volume14
Issue number1
DOIs
Publication statusPublished - 2005 Feb 1

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Virtual reality
Visualization
Semantics
Digital libraries
Distance education
Indentation
Clocks
Navigation
Display devices

All Science Journal Classification (ASJC) codes

  • Software
  • Control and Systems Engineering
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition

Cite this

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