Network theory

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

Topological Centrality and Its Applications

Abstract: Recent development of network structure analysis shows that it plays an important role in characterizing complex system of many branches of sciences. Different from previous network centrality measures, this paper proposes the notion of topological centrality (TC) reflecting the topological positions of nodes and edges in general networks, and proposes an approach to calculating the topological centrality. The proposed topological centrality is then used to discover communities and build the backbone network. Experiments and applications on research network show the significance of the proposed approach.

Attachment Centrality: An Axiomatic Approach to Connectivity in Networks

Abstract: Centrality indices aim to quantify the importance of nodes or edges in a network. A number of new centrality indices have recently been proposed to try and capture the role of nodes in connecting the network. While these indices seem to deliver new insights, to date not enough is known about their theoretical properties. To address this issue, we propose an axiomatic approach. Specifically, we prove that there exists a unique centrality index satisfying some intuitive properties related to network connectivity. This new index, which we call Attachment Centrality, is equivalent to the Myerson value of a particular graph-restricted coalitional game. Building upon our theoretical analysis, we show that our Attachment Centrality has certain computational properties that are more attractive than the Myerson value for an arbitrary game.

Strong-Ties and Weak-Ties Rationalities: Toward an Expanded Network Theory:

Abstract: This article introduces the expanded network theory and demonstrates the heuristic value of its construct of strong-ties and weak-ties rationalities. This construct is derived from the network theo...

The plant body as a network of semi-autonomous agents: a review.

Abstract: Plants can solve amazingly difficult tasks while adjusting their growth and development to the environment. They can explore and exploit several resources simultaneously, even when the distributions of these vary in space and time. The systematic study of plant behaviour goes back to Darwin's book The power of movement in plants. Current research has highlighted that modularity is a key to understanding plant behaviour, as the production, functional specialization and death of modules enable the plant to adjust its movement to the environment. The adjustment is assisted by a flow of information and resources among the modules. Experiments have yielded many results about these processes in various plant species. Theoretical research, however, has lagged behind the empirical studies, possibly owing to the lack of a proper modelling framework that could encompass the high number of components and interactions. In this paper, I propose such a framework on the basis of network theory, viewing the plant as a group of connected, semi-autonomous agents. I review some characteristic plant responses to the environment through changing the states of agents and/or links. I also point out some unexplored areas, in which a dialogue between plant science and network theory could be mutually inspiring. This article is part of the theme issue 'Liquid brains, solid brains: How distributed cognitive architectures process information'.

Betweeness-Centrality of Grid Networks

Abstract: Importance of estimating the centrality of the nodes in large networks has recently attracted increased interest. Betweenness is one of the most important centrality indices, which basically counts the number of shortest paths going through a node. Betweenness has been used in diverse applications such as social network analysis or route planning. In this paper we find a formula to obtain the betweeness-centrality for grids.