Introduction to Complex Networks: Structure and Dynamics

Estrada, Ernesto

doi:10.1007/978-3-319-11322-7_3

Cited by 50 publications

(39 citation statements)

References 50 publications

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“…If two nodes (node i and j) are linked to each other with the link e={i,j} in a network, then these nodes are said to be adjacent. Networks are represented with adjacency matrices which are built as follows (Estrada, 2015):…”

Section: Methodsmentioning

confidence: 99%

Network analysis of interbank cross-border flows at country level (2006 - 2015)

Eren¹,

Soyyiğit²

2017

Pressacademia

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In today's globalized world, economic activities are performed beyond the physical boundaries of countries. It can be seen as increasing activities such as trade of goods, financial flows and trade of intermediate goods. Network analysis, that has been used to analyze formations of complex systems recently, is frequently used to investigate these global economic relations. In this context, international trade networks, financial networks and global production networks (input-output networks) are some of the fields that are analyzed in an interdisciplinary way. In this study, it is aimed to analyze interbank cross-border flows at country-level by applying network analysis. Thus, we expect to investigate the systemic importance and vulnerabilities of countries in international banking sector by applying HITs algorithm from 2006 to 2015. HITs algorithm has an advantage since it takes second order adjacencies of countries into consideration. As a consequence of the analysis, it will be possible to see the effects of global and Eurozone crises on systemic importance and vulnerabilities of countries.

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Section: Methodsmentioning

confidence: 99%

Network analysis of interbank cross-border flows at country level (2006 - 2015)

Eren¹,

Soyyiğit²

2017

Pressacademia

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“…Modeling robustness of power grids against cascading failures is the main reason why many scientists and engineers have decided to apply the CN approach [51,[54][55][56][57][58][59][60][61][62] to power grids [8,13,14,[22][23][24][25]27,30,[34][35][36][63][64][65][66], these being a representative selection of the latest works in the field. Although it will be explained in Section 2 to make the manuscript self-completed, we introduce at this point the simple mathematical concept of network graph because it will assist us in better motivating the purpose of this paper and in explaining its structure.…”

Section: Stabilitymentioning

confidence: 99%

“…The CN approach has been used to explore the robustness, stability (see definition in Table 1), and resilience of different networks in highly cited papers such as [19,38,61,[67][68][69][70][71][72][73] and, more recently, in [74][75][76][77][78][79][80][81][82][83][84][85][86][87][88]. The key topic of network robustness (or vulnerability, the opposite property) has strongly attracted the attention of researchers in very different scientific and technological fields (physics, mathematics, biology, telecommunications, energy, economy,...) [51,55,[57][58][59][60][61][62]. In fact, cascading failures, described before as an apparently inherent potential weakness of electricity grids, are however common in complex networks regardless of whether they are integrated circuits, Internet, or transport networks, to name a few where the phenomenon is more noticeable [51,[57][58][59][60][61][89][90][91]…”

Section: Stabilitymentioning

confidence: 99%

A Critical Review of Robustness in Power Grids Using Complex Networks Concepts

et al. 2015

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This paper reviews the most relevant works that have investigated robustness in power grids using Complex Networks (CN) concepts. In this broad field there are two different approaches. The first one is based solely on topological concepts, and uses metrics such as mean path length, clustering coefficient, efficiency and betweenness centrality, among many others. The second, hybrid approach consists of introducing (into the CN framework) some concepts from Electrical Engineering (EE) in the effort of enhancing the topological approach, and uses novel, more efficient electrical metrics such as electrical betweenness, net-ability, and others. There is however a controversy about whether these approaches are able to provide insights into all aspects of real power grids. The CN community argues that the topological approach does not aim to focus on the detailed operation, but to discover the unexpected emergence of collective behavior, while part of the EE community asserts that this leads to an excessive simplification. Beyond this open debate it seems to be no predominant structure (scale-free, small-world) in high-voltage transmission power grids, the vast majority of power grids studied so far. Most of them have in common that they are vulnerable to targeted attacks on the most connected nodes and robust to random failure. In this respect there are only a few works that propose strategies to improve robustness such as intentional islanding, restricted link addition, microgrids and Energies 2015, 8 9212 smart grids, for which novel studies suggest that small-world networks seem to be the best topology.

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“…There are now many resources for learning about network ecology and network theory in general, and we point the reader in the direction of excellent reviews in this area (Proulx et al 2005, Ings et al 2009, Borrett et al 2012, Brandes et al 2013) and more comprehensive introductions (Brandes and Erlebach 2005, Newman 2010, Estrada 2015.…”

Section: A Primer Of Ecological Network: Models and Metricsmentioning

confidence: 99%

Ecological network metrics: opportunities for synthesis

et al. 2017

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Abstract. Network ecology provides a systems basis for approaching ecological questions, such as factors that influence biological diversity, the role of particular species or particular traits in structuring ecosystems, and long-term ecological dynamics (e.g., stability). Whereas the introduction of network theory has enabled ecologists to quantify not only the degree, but also the architecture of ecological complexity, these advances have come at the cost of introducing new challenges, including new theoretical concepts and metrics, and increased data complexity and computational intensity. Synthesizing recent developments in the network ecology literature, we point to several potential solutions to these issues: integrating network metrics and their terminology across sub-disciplines; benchmarking new network algorithms and models to increase mechanistic understanding; and improving tools for sharing ecological network research, in particular "model" data provenance, to increase the reproducibility of network models and analyses. We propose that applying these solutions will aid in synthesizing ecological sub-disciplines and allied fields by improving the accessibility of network methods and models.

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Introduction to Complex Networks: Structure and Dynamics

Cited by 50 publications

References 50 publications

Network analysis of interbank cross-border flows at country level (2006 - 2015)

Network analysis of interbank cross-border flows at country level (2006 - 2015)

A Critical Review of Robustness in Power Grids Using Complex Networks Concepts

Ecological network metrics: opportunities for synthesis

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