A secure and robust multilayer network with optimum inter layer links under budget constraints

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.

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Problems of Soft Budget Constraints in Intergovernmental Relationships: The Case of Italy

SSRN Electronic Journal ◽

10.2139/ssrn.1814671 ◽

2000 ◽

Cited By ~ 13

Author(s):

Massimo Bordignon

Keyword(s):

Budget Constraints ◽

Soft Budget Constraints ◽

Intergovernmental Relationships

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Soft Budget Constraints in a Federation: The Effect of Regional Affiliation

SSRN Electronic Journal ◽

10.2139/ssrn.2400428 ◽

2014 ◽

Author(s):

Willem Sas

Keyword(s):

Budget Constraints ◽

Soft Budget Constraints ◽

Regional Affiliation

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Multilayer Network Valuation with Equity Conversions

SSRN Electronic Journal ◽

10.2139/ssrn.3225943 ◽

2018 ◽

Author(s):

Matias Puig ◽

Christoph Siebenbrunner

Keyword(s):

Multilayer Network

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Diffusion

10.1093/oso/9780198753919.003.0014 ◽

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.

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Centrality Measures

10.1093/oso/9780198753919.003.0009 ◽

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.

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The (Non) Economic Properties of the Law

Games ◽

10.3390/g12010026 ◽

2021 ◽

Vol 12 (1) ◽

pp. 26

Author(s):

Leo Katz ◽

Alvaro Sandroni

Keyword(s):

Economic Theory ◽

Bounded Rationality ◽

Budget Constraints ◽

The Law

This paper shows that the logical properties of constraints imposed by law are fundamentally different from other constraints considered in economics such as budget constraints and bounded rationality constraints, such as the ones based on inattention or shortlisting. This suggests that to fully incorporate law into economics may require a revision of economic theory.

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The structure of co-publications multilayer network

Computational Social Networks ◽

10.1186/s40649-021-00089-w ◽

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.

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