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Visualization of Evolving Social Networks using Actor-Level and Community-Level Trajectories

Author

Listed:
  • Márcia Oliveira

    (LIAAD/INESC TEC e Faculdade de Economia, Universidade do Porto)

  • João Gama

    (LIAAD/INESC TEC e Faculdade de Economia, Universidade do Porto)

Abstract

In recent years we witnessed an impressive advance in the social networks field, which became a "hot" topic and a focus of considerable attention. Also, the development of methods that focus on the analysis and understanding of the evolution of data are gaining momentum. In this paper we present an approach to visualize the evolution of dynamic social networks by using Tucker decomposition and the concept of temporal trajectory. Our visualization strategy is based on the definition of trajectories, both at the node-level and at the community-level, in a bidimensional space that preserves its structural properties. Furthermore, this approach can be used to identify similar actors, or communities of actors, by comparing the shape and position of trajectories. To illustrate the proposed approach we conduct a case study using a set of temporal friendship networks.

Suggested Citation

  • Márcia Oliveira & João Gama, 2012. "Visualization of Evolving Social Networks using Actor-Level and Community-Level Trajectories," FEP Working Papers 446, Universidade do Porto, Faculdade de Economia do Porto.
    • Handle: RePEc:por:fepwps:446
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    More about this item

    Keywords

    Data Evolution; Data Visualization; Social Networks; Trajectories; Tucker3 model;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis

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