New coordination method of multilayer network survivability

2002 ◽  
Author(s):  
Jihong Zhao ◽  
Hua Qu
Keyword(s):  
Network Survivability ◽  
Multilayer Network

A performative network theory of attitudes

2020 ◽  
Author(s):  
Michael Quayle
Keyword(s):  
Attitude Change ◽  
Network Structure ◽  
Network Theory ◽  
Social Group ◽  
Group Structure ◽  
Social Identities ◽  
Bipartite Network ◽  
Identity Change ◽  
Multilayer Network ◽  
Dynamic Phenomena

In this paper I propose a network theory of attitudes where attitude agreements and disagreements forge a multilayer network structure that simultaneously binds people into groups (via attitudes) and attitudes into clusters (via people who share them). This theory proposes that people have a range of possible attitudes (like cards in a hand) but these only become meaningful when expressed (like a card played). Attitudes are expressed with sensitivity to their potential audiences and are socially performative: when we express attitudes, or respond to those expressed by others, we tell people who we are, what groups we might belong to and what to think of us. Agreement and disagreement can be modelled as a bipartite network that provides a psychological basis for perceived ingroup similarity and outgroup difference and, more abstractly, group identity. Opinion-based groups and group-related opinions are therefore co-emergent dynamic phenomena. Dynamic fixing occurs when particular attitudes become associated with specific social identities. The theory provides a framework for understanding identity ecosystems in which social group structure and attitudes are co-constituted. The theory describes how attitude change is also identity change. This has broad relevance across disciplines and applications concerned with social influence and attitude change.

Multilayer Network Valuation with Equity Conversions

2018 ◽  
Author(s):  
Matias Puig ◽  
Christoph Siebenbrunner
Keyword(s):  
Multilayer Network

Diffusion

2018 ◽  
Author(s):  
Ginestra Bianconi
Keyword(s):  
Random Walks ◽  
Spectral Properties ◽  
Diffusion Constant ◽  
Network Structures ◽  
Multilayer Networks ◽  
Multilayer Network ◽  
Lévy Walk ◽  
Number Of Layers ◽  
Levy Walk ◽  
Speed Up

This chapter addresses diffusion, random walks and congestion in multilayer networks. Here it is revealed that diffusion on a multilayer network can be significantly speed up with respect to diffusion taking place on its single layers taken in isolation, and that sometimes it is possible also to observe super-diffusion. Diffusion is here characterized on multilayer network structures by studying the spectral properties of the supra-Laplacian and the dependence on the diffusion constant among different layers. Random walks and its variations including the Lévy Walk are shown to reflect the improved navigability of multilayer networks with more layers. These results are here compared with the results of traffic on multilayer networks that, on the contrary, point out that increasing the number of layers could be detrimental and could lead to congestion.

Centrality Measures

2018 ◽  
Author(s):  
Ginestra Bianconi
Keyword(s):  
State Of The Art ◽  
Centrality Measures ◽  
Eigenvector Centrality ◽  
Multilayer Networks ◽  
Comprehensive Description ◽  
Multilayer Network ◽  
Suitable Definition ◽  
Katz Centrality ◽  
Pagerank Centrality

Defining the centrality of nodes and layers in multilayer networks is of fundamental importance for a variety of applications from sociology to biology and finance. This chapter presents the state-of-the-art centrality measures able to characterize the centrality of nodes, the influences of layers or the centrality of replica nodes in multilayer and multiplex networks. These centrality measures include modifications of the eigenvector centrality, Katz centrality, PageRank centrality and Communicability to the multilayer network scenario. The chapter provides a comprehensive description of the research of the field and discusses the main advantages and limitations of the different definitions, allowing the readers that wish to apply these techniques to choose the most suitable definition for his or her case study.

scholarly journals The structure of co-publications multilayer network

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Ghislain Romaric Meleu ◽  
Paulin Yonta Melatagia
Keyword(s):  
Power Law ◽  
Degree Distribution ◽  
Preferential Attachment ◽  
Small World ◽  
Generation Model ◽  
Small World Network ◽  
Power Law Distribution ◽  
Multilayer Networks ◽  
Multilayer Network ◽  
Scientific Papers

AbstractUsing the headers of scientific papers, we have built multilayer networks of entities involved in research namely: authors, laboratories, and institutions. We have analyzed some properties of such networks built from data extracted from the HAL archives and found that the network at each layer is a small-world network with power law distribution. In order to simulate such co-publication network, we propose a multilayer network generation model based on the formation of cliques at each layer and the affiliation of each new node to the higher layers. The clique is built from new and existing nodes selected using preferential attachment. We also show that, the degree distribution of generated layers follows a power law. From the simulations of our model, we show that the generated multilayer networks reproduce the studied properties of co-publication networks.

scholarly journals Frequent Itemset Mining and Multi-Layer Network-Based Analysis of RDF Databases

Mathematics ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 450
Author(s):  
Gergely Honti ◽  
János Abonyi
Keyword(s):  
Climate Change ◽  
Extraction Process ◽  
Knowledge Extraction ◽  
Frequent Itemset ◽  
Frequent Itemset Mining ◽  
Underlying Structure ◽  
Multilayer Network ◽  
Interdisciplinary Science ◽  
Academic Knowledge ◽  
Itemset Mining

Triplestores or resource description framework (RDF) stores are purpose-built databases used to organise, store and share data with context. Knowledge extraction from a large amount of interconnected data requires effective tools and methods to address the complexity and the underlying structure of semantic information. We propose a method that generates an interpretable multilayered network from an RDF database. The method utilises frequent itemset mining (FIM) of the subjects, predicates and the objects of the RDF data, and automatically extracts informative subsets of the database for the analysis. The results are used to form layers in an analysable multidimensional network. The methodology enables a consistent, transparent, multi-aspect-oriented knowledge extraction from the linked dataset. To demonstrate the usability and effectiveness of the methodology, we analyse how the science of sustainability and climate change are structured using the Microsoft Academic Knowledge Graph. In the case study, the FIM forms networks of disciplines to reveal the significant interdisciplinary science communities in sustainability and climate change. The constructed multilayer network then enables an analysis of the significant disciplines and interdisciplinary scientific areas. To demonstrate the proposed knowledge extraction process, we search for interdisciplinary science communities and then measure and rank their multidisciplinary effects. The analysis identifies discipline similarities, pinpointing the similarity between atmospheric science and meteorology as well as between geomorphology and oceanography. The results confirm that frequent itemset mining provides an informative sampled subsets of RDF databases which can be simultaneously analysed as layers of a multilayer network.

scholarly journals Species functional traits and abundance as drivers of multiplex ecological networks: first empirical quantification of inter-layer edge weights

2020 ◽  
Vol 287 (1939) ◽  
pp. 20202127
Author(s):  
S. Hervías-Parejo ◽  
C. Tur ◽  
R. Heleno ◽  
M. Nogales ◽  
S. Timóteo ◽  
...  
Keyword(s):  
Species Traits ◽  
Abundant Species ◽  
Modular Organization ◽  
Vertebrate Species ◽  
Multilayer Network ◽  
Functional Roles ◽  
Different Types ◽  
Seed Dispersers ◽  
Natural Communities

Many vertebrate species act as both plant pollinators and seed-dispersers, thus interconnecting these processes, particularly on islands. Ecological multilayer networks are a powerful tool to explore interdependencies between processes; however, quantifying the links between species engaging in different types of interactions (i.e. inter-layer edges) remains a great challenge. Here, we empirically measured inter-layer edge weights by quantifying the role of individually marked birds as both pollinators and seed-dispersers of Galápagos plant species over an entire year. Although most species (80%) engaged in both functions, we show that only a small proportion of individuals actually linked the two processes, highlighting the need to further consider intra-specific variability in individuals' functional roles. Furthermore, we found a high variation among species in linking both processes, i.e. some species contribute more than others to the modular organization of the multilayer network. Small and abundant species are particularly important for the cohesion of pollinator seed-dispersal networks, demonstrating the interplay between species traits and neutral processes structuring natural communities.

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