The Architecture of a Novel Weighted Network: Knowledge Network

TL;DR

This paper introduces a novel weighted knowledge network to analyze the topological and hierarchical structure of knowledge systems, highlighting the relationship between edge intensities and network topology.

Contribution

It constructs the first detailed weighted knowledge network and explores how edge weights relate to the network's topological features, offering new insights into knowledge system organization.

Findings

Uncovered the hierarchical structure of the knowledge network.

Established the relationship between edge weights and network topology.

Provided a new paradigm for studying weighted networks.

Abstract

Networked structure emerged from a wide range of fields such as biological systems, World Wide Web and technological infrastructure. A deeply insight into the topological complexity of these networks has been gained. Some works start to pay attention to the weighted network, like the world-wide airport network and the collaboration network, where links are not binary, but have intensities. Here, we construct a novel knowledge network, through which we take the first step to uncover the topological structure of the knowledge system. Furthermore, the network is extended to the weighted one by assigning weights to the edges. Thus, we also investigate the relationship between the intensity of edges and the topological structure. These results provide a novel description to understand the hierarchies and organizational principles in knowledge system, and the interaction between the intensity of edges and topological structure. This system also provides a good paradigm to study weighted networks.