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Visualisation of structure and processes on temporal networks

Visualisation of structure and processes on temporal networks

Linhares, Claudio, Ponciano, Jean, Paiva, Jose Gustavo, Travencolo, Bruno and Correa Da Rocha, Luis ORCID: 0000-0001-9046-8739 (2019) Visualisation of structure and processes on temporal networks. In: Holme, Petter and Saramaki, Jari, (eds.) Temporal Network Theory. Computational Social Sciences . Springer, Switzerland. ISBN 978-3030234942 (In Press)

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Abstract

The temporal dimension increases the complexity of network models but also provides more detailed information about the sequence of connections between nodes allowing a more detailed mapping of processes taking place on the network. The visualisation of such evolving structures thus permits faster identification of non-trivial activity patterns and provides insights about the mechanisms driving the dynamics on and of networks. In this chapter, we introduce key concepts and discuss visualisation methods of temporal networks based on 2D layouts where nodes correspond to horizontal lines with circles to represent active nodes and vertical edges connecting those active nodes at given times. We introduce and discuss algorithms to re-arrange nodes and edges to reduce visual clutter, layouts to highlight node and edge activity, and visualise dynamic processes on temporal networks. We illustrate the methods using real-world temporal network data of face-to-face human contacts and simulated random walk and infection dynamics.

Item Type: Book Section
Uncontrolled Keywords: Network Visualisation; Network Science; Information Visualisation; Temporal Networks; Time-varying networks; Dynamic networks; contact networks; random walks; epidemics
Subjects: H Social Sciences > H Social Sciences (General)
Faculty / Department / Research Group: Faculty of Business
Faculty of Business > Department of International Business & Economics
Faculty of Business > Networks and Urban Systems Centre (NUSC)
Faculty of Business > Networks and Urban Systems Centre (NUSC) > Centre for Business Network Analysis (CBNA)
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Last Modified: 01 Oct 2019 10:16
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
URI: http://gala.gre.ac.uk/id/eprint/24708

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