Network theory

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

Some characteristics of supernetworks based on unified hybrid network theory framework

Abstract: Comparing with single complex networks, supernetworks are more close to the real world in some ways, and have become the newest research hot spot in the network science recently. Some progresses ha...

A Network Based Theory of Health Systems and Cycles of Well-Being

Abstract: There are two dominant approaches to describe and understand the anatomy of complete health and well-being systems internationally. Yet, neither approach has been able to either predict or explain occasional but dramatic crises in health and well-being systems around the world and in developed emerging market or developing country contexts. As the impacts of such events can be measured not simply in terms of their social and economic consequences but also public health crises, there is a clear need to look for and formulate an alternative approach. This paper examines multi-disciplinary theoretical evidence to suggest that health systems exhibit natural and observable systemic and long cycle characteristics that can be modelled. A health and well-being system model of two slowly evolving anthropological network sub-systems is defined. The first network sub-system consists of organised professional networks of exclusive suppliers of health and well-being services. The second network sub-system consists of communities organising themselves to resource those exclusive services. Together these two network sub-systems interact to form the specific (sovereign) health and well-being systems we know today. But the core of a truly ‘complex adaptive system’ can also be identified and a simplified two sub-system model of recurring Lotka-Volterra predator-prey cycles is specified. The implications of such an adaptive and evolving model of system anatomy for effective public health, social security insurance and well-being systems governance could be considerable

Symbolic Function Network: Theory and Implementation

Abstract: This chapter reviews a recent HONN-like model called Symbolic Function Network (SFN). This model is designed with the goal to impart more flexibility than both traditional and HONNs neural networks. The main idea behind this scheme is the fact that different functional forms suit different applications and that no specific architecture is best for all. Accordingly, the model is designed as an evolving network that can discover the best functional basis, adapt its parameters, and select its structure simultaneously. Despite the high modeling capability of SFN, it is considered as a starting point for developing more powerful models. This chapter aims to open a door for researchers to propose new formulations and techniques that impart more flexibility and result in sparser and more accurate models. Through this chapter, the theoretical basis of SFN is discussed. The model optimization computations are deeply illustrated to enable researchers to easily implement and test the model.

Dependency Centrality from Bipartite Social Networks

Abstract: This paper introduces dependency centrality, a node-level measure of structural leadership in bipartite networks. The measure builds on Zhou et al.’s (2007) flow-based method to transform bipartite data and captures additional information from the second mode that existing measures of centrality typically exclude. Three previously published bipartite networks serve as test cases to demonstrate the extent of correlation among node-level centrality rankings derived from dependency centrality and those derived from canonical centrality measures: degree, closeness, betweenness, and eigenvector. Ultimately, dependency centrality appears to offer a novel means to measure importance in bipartite networks depicting social interactions. Author Luke M. Gerdes is an Assistant Professor in the Department of Behavioral Sciences & Leadership at the United States Military Academy in West Point, New York. Notes This work was supported by the Office of the Secretary of Defense, Minerva Initiative. The views expressed herein are those of the author and do not purport to represent the official policy or position of the United States Military Academy, the Department of the Army, the Department of Defense, or the United States Government. Please send all correspondence to Luke M. Gerdes, Department of Behavioral Sciences & Leadership, United States Military Academy. Email: luke.gerdes@usma.edu