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Network theory

About: Network theory is a research topic. Over the lifetime, 2257 publications have been published within this topic receiving 109864 citations.


Papers
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Proceedings ArticleDOI
01 Apr 2017
TL;DR: This paper proposes a new approach in identifying a network centrality based on a many-objective optimization approach, where the nodes are the potential points to be selected and the objectives are their centrality in the different layers of the network.
Abstract: Network centrality plays an important role in network analysis — especially in social and economic network analysis such as identification of the most popular actor and artist in the Hollywood community, or to find the most influential scientist in a citation network, or politician in democratic elections. Furthermore, finding an important player for the growth of economics in a region can be important to improve future welfare, or to find important hubs for spreading an important message in crisis management. Many algorithms have been proposed to identify a set of key players in a single network. But in the real world with more complicated data sets we need not only to identify a single player but a set of key players. Moreover, we may have to use different types of links simultaneously, e.g., different social networks, in order to define how influential a node is. This situation can be modelled by multiplex network data. For a multiplex network the set of nodes stays the same, while there are multiple sets of edges. The utilization of such information can be viewed as a multiple objective decision analysis problem. In this paper, we propose a new approach in identifying a network centrality based on a many-objective optimization approach, where the nodes are the potential points to be selected and the objectives are their centrality in the different layers of the network. This yields a new approach to analyse network centrality in multiplex network. For this approach, we propose to compute the Pareto fronts of network centrality of nodes, where maximization of centrality in layer defines its own objective. As a case study, we compute the Pareto fronts for model problems with artificial network and real networks for economic data sets to show on how to find the network centrality trade-offs between different layers and identify efficient sets of key nodes.

3 citations

Book ChapterDOI
30 May 2009
TL;DR: It was found that the major changes in the structure of the network concern its local topology, which changes significantly which may be detected with motif analysis and visible changes in node clustering coefficients.
Abstract: Different ways of detecting structural changes in email-based social networks are presented in the paper. A social network chosen for experiments was created on the basis of the Wroclaw University of Technology email server logs covering the period of 20 months. Structural parameters like degree centrality and prestige, clustering coefficients as well as betweenness and closeness centrality were computed for each of the consecutive months and their changes were analyzed. Our aim was to make an insight into dynamics of Internet-based social networks based on email service. It was found that the major changes in the structure of the network concern its local topology. Global indices like betweenness and closeness centrality remain relatively stable which also concerns the distribution of the local parameters such as degree centrality and prestige. However, the network size and local topology changes significantly which may be detected with motif analysis and visible changes in node clustering coefficients.

3 citations

01 Oct 2014
TL;DR: The results show that the proposed model can not only describe the route choice behavior in the multimodal transportation network, but also get the departure time, which comes closer to the reality and has good suitability.
Abstract: The dynamic route choice model with departure time was carried out in a multi-modal transportation network, in which the combined travel mode was considered. The multi-modal transportation network was built based on the super network theory and the expansion technique. The simultaneous departure time and the route choice preference were described in a Logit model from the view of path formulation, as well as analyzing the equilibrium conditions. A variational inequality model was proposed to be equivalent to the equilibrium condition and was solved by a direct algorithm based on a dynamic stochastic network loading method. The efficient of the model and the algorithm were validated by a numerical example. The results show that the proposed model can not only describe the route choice behavior in the multimodal transportation network, but also get the departure time, which comes closer to the reality and has good suitability.

3 citations

12 Oct 2020
TL;DR: A representation of the space environment as a dynamic multilayer network, where space objects are nodes and their relationships are captured through dynamic links; each layer represents a different type of interaction.
Abstract: With the advent of the New Space era and the increase in the population of resident objects in Earth orbit, there is a compelling need to adopt new tools to study the complexity of the space environment. In particular, there is a need to consider the different layers of functionalities and services in an integrated and consistent framework that allows a global analysis of the evolution of the space environment. In the past two decades, there has been intense research to describe and model physical, engineering, information, social and biological systems using network theory. Most recently, multilayer networks, or networks of networks, have demonstrated a higher capability of describing failures, relationships, connectivity, and patterns, with respect to their single-layer counterpart. This paper presents a representation of the space environment as a dynamic multilayer network, where space objects are nodes and their relationships are captured through dynamic links; each layer represents a different type of interaction. In this paper, in particular, we consider two layers: the physical and the information layer. The former models the collision between pairs of objects and how disruptions tend to propagate in the network, while the latter models the exchange of information among satellites via telecommunication. Links are probabilistic in that they model the probability of an interaction between two nodes. Moreover, the spreading dynamics of disruptions among nodes is mathematically described with a susceptible-infectious-susceptible epidemiological model. By using a bottom-up approach, where we stochastically simulate the spreading of a disruptive event in the network, we show how it is possible to investigate different spreading scenarios and analyze the network weak links and nodes, which can then be targeted for improving the space environment resilience.

3 citations

01 Jan 2009
TL;DR: In this paper, the authors make the problem of space in social networks explicit by proposing a surprising analogy with the question: what do you have to add to an urban space network to get a city?
Abstract: Recent years have seen great advances in social network analysis. Yet, with a few exceptions, the field of network analysis remains remote from social theory. As a result, much social network research, while technically accomplished and theoretically suggestive, is essentially descriptive. How then can social networks be linked to social theory ? Here we pose the question in its simplest form: what must we add to a social network to get a society ? We begin by showing that one reason for the disconnection between network theory and society theory is that because it exists in spacetime, the concept of social network raises the issue of space in a way that is problematical for social theory. Here we turn the problem on its head and make the problem of space in social network theory explicit by proposing a surprising analogy with the question: what do you have to add to an urban space network to get a city. We show first that by treating a city as a naive spatial network in the first instance and allowing it to acquire two formal properties we call reflexivity and nonlocality, both mediated through a mechanism we call description retrieval, we can build a picture of the dynamics processes by which collections of the buildings become living cities. We then show that by describing societies initially as social networks in space-time and adding similar properties, we can construct a plausible ontology of a simple human society.

3 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202319
202240
202175
2020109
201989
2018115