Federico, P., Aigner, W., Miksch, S., Windhager, F., & Zenk, L. (2011). A visual analytics approach to dynamic social networks. In Proceedings of the 11th International Conference on Knowledge Management and Knowledge Technologies - i-KNOW ’11. International Conference on Knowledge Management and Knowledge Technologies (I-KNOW), Special Track on Theory and Applications of Visual Analytics (TAVA), Graz, Austria. ACM. https://doi.org/10.1145/2024288.2024344
Proceedings of the 11th International Conference on Knowledge Management and Knowledge Technologies - i-KNOW '11
International Conference on Knowledge Management and Knowledge Technologies (I-KNOW), Special Track on Theory and Applications of Visual Analytics (TAVA)
Number of Pages:
information visualization; visual analytics; interaction; social network analysis; graph drawing; dynamic layout; dynamic networks
The visualization and analysis of dynamic networks have become increasingly important in several fields, for instance sociology or economics. The dynamic and multi-relational nature of this data poses the challenge of understanding both its topological structure and how it changes over time. In this paper we propose a visual analytics approach for analyzing dynamic networks that integrates: a dynamic layout with user-controlled trade-off between stability and consistency; three temporal views based on different combinations of node-link diagrams (layer superimposition, layer juxtaposition, and two-and-a-half dimensional view); the visualization of social network analysis metrics; and specific interaction techniques for tracking node trajectories and node connectivity over time. This integration of visual, interactive, and automatic methods supports the multifaceted analysis of dynamically changing networks.
CVAST: Centre for Visual Analytics Science and Technology (Laura Bassi Centre of Expertise) VIENA: Visual Enterprise Network Analytics (FFG - Österr. Forschungsförderungs- gesellschaft mbH)
Business Informatics: 50% Visual Computing and Human-Centered Technology: 50%