Towards a process-driven network analysis
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(2020) 5:56
Applied Network Science
RESEARCH
Open Access
Towards a process-driven network analysis Mareike Bockholt*
and Katharina Anna Zweig
*Correspondence: [email protected] Algorithm Accountability Lab, Department of Computer Science, University of Kaiserslautern, Kaiserslautern, Germany
Abstract A popular approach for understanding complex systems is a network analytic one: the system’s entities and their interactions are represented by a graph structure such that readily available methods suitable for graph structures can be applied. A network representation of a system enables the analysis of indirect effects: if A has an impact on B, and B has an impact on C, then, A also has an impact on C. This is often due to some kind of process flowing through the network, for example, pieces of informations or viral infections in social systems, passenger flows in transportation systems, or traded goods in economic systems. We argue that taking into account the actual usage of the system additionally to the static network representation of the system can yield interesting insights: first, the network representation and applicable network methods cannot be chosen independently from the network process of interest (Borgatti 2005; Dorn et al. 2012; Zweig 2016; Butts 2009). Therefore, focussing on the relevant network process in an early stage of the research project helps to determine suitable network representations and methods in order to obtain meaningful results (we call this approach process-driven network analysis). Second, many network methods assume that the spreading of some entity follows shortest or random paths. However, we show that not all flows are well approximated by this. In these cases, incorporating the network usage creates a real addition of knowledge to the static aggregated network representation. Note: This is an extended and revised version of a conference article (Bockholt and Zweig 2019), published and presented at COMPLEX NETWORKS 2019. Keywords: Network process, Process models, Network representation, Human navigation
Introduction In the past two decades, the interest in complex systems has risen tremendously. Examples of complex systems include social systems of humans, biological systems of protein-protein-interactions, or transportation systems as the world-wide air transportation system. A popular and often natural approach for analyzing such systems is using network analysis (Boccaletti et al. 2006; Brandes et al. 2005) (see also Fig. 1): The interactions in the system are observed, these observations are then used to create a network representation of the system, i.e., a graph structure. For the network representation of © The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and
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