Opinion Dynamics and Game Theory

2018 ◽  
Author(s):  
Ginestra Bianconi
Keyword(s):  
Game Theory ◽  
Social Systems ◽  
Single Layer ◽  
Opinion Dynamics ◽  
Structure And Function ◽  
Voter Model ◽  
Multilayer Networks ◽  
Multilayer Network ◽  
The Rich ◽  
And Function

This chapter is devoted to opinion dynamics and game theory on multilayer networks. Since in social systems multilayer networks are the rule, it is particularly relevant to extend the modelling opinion dynamics to the multilayer network scenario. This chapter focuses in particular on the Voter Model, its variants, the Co-evolving Voter Model and models of competing networks, including election models showing that multiplexity has a major role in determining opinion dynamics. In particular, opinion dynamics on multilayer networks is not reducible to opinion dynamics on single layer networks. Finally, the rich interplay between structure and function in multilayer networks is discussed in the framework of game theory.

Complex Systems as Multilayer Networks

2018 ◽  
Author(s):  
Ginestra Bianconi
Keyword(s):  
Complex Systems ◽  
Information Gain ◽  
Single Layer ◽  
Multilayer Networks ◽  
Research Activity ◽  
Multilayer Network ◽  
New Development ◽  
The Rich ◽  
And Function

Chapter 1 constitutes Part I of the book: ‘Single and Multilayer Networks’. This chapter introduces multilayer networks as an important new development of Network Science that allows a more comprehensive understanding of Complex Systems. It identifies the main motivations driving the research activity in this field of multilayer networks and emphasizes the benefits of taking a multilayer network perpective to characterize network data. The main advantages of a multilayer network approach with respect to the more traditional single layer characterization of complex networks are broadly discussed, focusing on the information gain resulting from the analysis of multilayer networks, the non-reducibility of a multilayer network to a large single network and the rich interplay between structure and function in multilayer networks.

scholarly journals A tensor-based framework for studying eigenvector multicentrality in multilayer networks

2019 ◽  
Vol 116 (31) ◽  
pp. 15407-15413 ◽  
Author(s):  
Mincheng Wu ◽  
Shibo He ◽  
Yongtao Zhang ◽  
Jiming Chen ◽  
Youxian Sun ◽  
...  
Keyword(s):  
Complex Networks ◽  
Prior Knowledge ◽  
General Framework ◽  
Single Layer ◽  
Structure And Function ◽  
Centrality Measures ◽  
Multilayer Networks ◽  
And Function ◽  
The Impact ◽  
Insight Into

Centrality is widely recognized as one of the most critical measures to provide insight into the structure and function of complex networks. While various centrality measures have been proposed for single-layer networks, a general framework for studying centrality in multilayer networks (i.e., multicentrality) is still lacking. In this study, a tensor-based framework is introduced to study eigenvector multicentrality, which enables the quantification of the impact of interlayer influence on multicentrality, providing a systematic way to describe how multicentrality propagates across different layers. This framework can leverage prior knowledge about the interplay among layers to better characterize multicentrality for varying scenarios. Two interesting cases are presented to illustrate how to model multilayer influence by choosing appropriate functions of interlayer influence and design algorithms to calculate eigenvector multicentrality. This framework is applied to analyze several empirical multilayer networks, and the results corroborate that it can quantify the influence among layers and multicentrality of nodes effectively.

Interdependent Multilayer Networks

2018 ◽  
Author(s):  
Ginestra Bianconi
Keyword(s):  
Complex Systems ◽  
Network Structure ◽  
Structure And Function ◽  
Molecular Networks ◽  
Multilayer Networks ◽  
Multilayer Network ◽  
Interdependent Networks ◽  
Multiplex Networks ◽  
And Function

This chapter characterizes interdependent multilayer networks and their increased fragility. Interdependent networks are stylized models that can represent different complex systems, ranging from global infrastructures to molecular networks in the cell. When a fraction of nodes is initially damaged, interdependent networks are affected by dramatic cascades of failures that suddenly dismantle the multilayer network. The theory beyond this phenomenology is discussed in a pedagogical way by characterizing the percolation, discontinuous and hybrid transitions. The interplay between structure and function is studied in this context by considering multiplex networks without and with link overlap, and the effect of built-in correlations in the multilayer network structure. Finally, partial interdependencies and redundant interdependencies are discussed as major strategies to reduce the fragility of interdependent networks.

scholarly journals Multilayer network analyses as a toolkit for measuring social structure

2021 ◽  
Vol 67 (1) ◽  
pp. 81-99
Author(s):  
Kelly R Finn
Keyword(s):  
Social Structure ◽  
Social Systems ◽  
Deep Understanding ◽  
Single Layer ◽  
Mathematical Representation ◽  
Multilayer Networks ◽  
Multilayer Network ◽  
Network Analyses ◽  
Different Types ◽  
Multilayer Social Networks

Abstract The formalization of multilayer networks allows for new ways to measure sociality in complex social systems, including groups of animals. The same mathematical representation and methods are widely applicable across fields and study systems, and a network can represent drastically different types of data. As such, in order to apply analyses and interpret the results in a meaningful way the researcher must have a deep understanding of what their network is representing and what parts of it are being measured by a given analysis. Multilayer social networks can represent social structure with more detail than is often present in single layer networks, including multiple “types” of individuals, interactions, or relationships, and the extent to which these types are interdependent. Multilayer networks can also encompass a wider range of social scales, which can help overcome complications that are inherent to measuring sociality. In this paper, I dissect multilayer networks into the parts that correspond to different components of social structures. I then discuss common pitfalls to avoid across different stages of multilayer network analyses—some novel and some that always exist in social network analysis but are magnified in multi-layer representations. This paper serves as a primer for building a customized toolkit of multilayer network analyses, to probe components of social structure in animal social systems.

State-of-the-Art Neural Networks Applications in Biology

2013 ◽  
Vol 2 (4) ◽  
pp. 63-85 ◽  
Author(s):  
Arianna Filntisi ◽  
Nikitas Papangelopoulos ◽  
Elena Bencurova ◽  
Ioannis Kasampalidis ◽  
George Matsopoulos ◽  
...  
Keyword(s):  
Neural Networks ◽  
Game Theory ◽  
State Of The Art ◽  
Disease Diagnosis ◽  
General Term ◽  
Structure And Function ◽  
Computational Method ◽  
Processing Abilities ◽  
Central Nervous Systems ◽  
And Function

Artificial neural networks (ANNs) are a well-established computational method inspired by the structure and function of biological central nervous systems. Since their conception, ANNs have been utilized in a vast variety of applications due to their impressive information processing abilities. A vibrant field, ANNs have been utilized in bioinformatics, a general term for describing the combination of informatics, biology and medicine. This article is an effort to investigate recent advances in the area of bioinformatical applications of ANNs, with emphasis in disease diagnosis, genetics, proteomics, and chemoinformatics. The combination of neural networks and game theory in some of these application is also discussed.

OPINION DIFFUSION ON MULTILAYER SOCIAL NETWORKS

2017 ◽  
Vol 20 (06n07) ◽  
pp. 1750015 ◽  
Author(s):  
HAI-BO HU ◽  
CANG-HAI LI ◽  
QING-YING MIAO
Keyword(s):  
Social Networks ◽  
Opinion Dynamics ◽  
Coupling Agents ◽  
Dynamics Model ◽  
Multilayer Networks ◽  
Multilayer Network ◽  
Influence Matrix ◽  
Strongly Connected ◽  
Degroot Model ◽  
Multilayer Social Networks

In this paper, to reveal the influence of multilayer network structure on opinion diffusion in social networks, we study an opinion dynamics model based on DeGroot model on multilayer networks. We find that if the influence matrix integrating the information of connectedness for each layer and correlation between layers is strongly connected and aperiodic, all agents’ opinions will reach a consensus. However, if there are stubborn agents in the networks, regular agents’ opinions will finally be confined to the convex combinations of the stubborn agents’. Specifically, if all stubborn agents hold the same opinion, even if the agents only exist on a certain layer, their opinions will diffuse to the entire multilayer networks. This paper not only characterizes the influence of multilayer network topology and agent attribute on opinion diffusion in a holistic way, but also demonstrates the importance of coupling agents which play an indispensable role in some social and economic situations.

Mammalian social systems: Structure and function

1976 ◽  
Vol 24 (2) ◽  
pp. 261-274 ◽  
Author(s):  
J.H. Crook ◽  
J.E. Ellis ◽  
J.D. Goss-Custard
Keyword(s):  
Social Systems ◽  
Structure And Function ◽  
And Function

scholarly journals Successes, challenges, and opportunities for quantum chemistry in understanding metalloenzymes for solar fuels research

2021 ◽  
Vol 57 (33) ◽  
pp. 3952-3974
Author(s):  
Maylis Orio ◽  
Dimitrios A. Pantazis
Keyword(s):  
Photosystem Ii ◽  
Quantum Chemistry ◽  
Structure And Function ◽  
Solar Fuels ◽  
Solar Fuel ◽  
Challenges And Opportunities ◽  
The Rich ◽  
And Function

Overview of the rich and diverse contributions of quantum chemistry to understanding the structure and function of the biological archetypes for solar fuel research, photosystem II and hydrogenases.

Post-conflict initiatives and the exclusion of conflict-affected young people in northern Uganda

2021 ◽  
Vol 59 (1) ◽  
pp. 21-39
Author(s):  
Alina Dixon
Keyword(s):  
Young People ◽  
Family System ◽  
Social Systems ◽  
Structure And Function ◽  
Northern Uganda ◽  
Social Environments ◽  
Post Conflict ◽  
The Family ◽  
And Function

ABSTRACTYoung people are among the most severely impacted by conflict and as such many post-conflict initiatives are aimed at assisting them. Yet the impacts of these initiatives on young people's ability to successfully overcome the adversity they faced during conflict are not fully understood. This paper attempts to examine these impacts by conceptualising post-conflict initiatives as enmeshed within young people's social environments. It argues that post-conflict initiatives are intimately connected to broader processes of exclusion from social systems such as the family. While these systems had previously served to protect young people against adversity, conflict and post-conflict initiatives have disrupted their ability to continue this mission. In particular, the structure and function of the family system are examined to demonstrate the types of disruptions that have taken place that have ultimately negatively impacted the landscape in which young people develop.

"Situational" Interactions - A Worthwhile Concept?

1958 ◽  
Vol 17 (4) ◽  
pp. 37-47 ◽  
Author(s):  
Frank Miller
Keyword(s):  
Systematic Study ◽  
Social Systems ◽  
Structure And Function ◽  
Work Organizations ◽  
And Function

Systematic study of the structure and function of organizations was advanced impressively by the application and elaboration of the concept interaction. Social systems have been described in terms of who interacts with whom, how often they interact, and the extent to which individuals originate or respond in these interactions. In describing industrial and other work organizations, four types of interaction linkages ("sets") are frequently considered as the important components to examine.1 They are the interactions between:

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