TY - JOUR

T1 - A Simple Visualization Method for Three-Dimensional (3D) Network

AU - Kim, Sangkwon

AU - Lee, Chaeyoung

AU - Park, Jintae

AU - Yoon, Sungha

AU - Choi, Yongho

AU - Kim, Junseok

N1 - Publisher Copyright:
© 2021 Sangkwon Kim et al.

PY - 2021

Y1 - 2021

N2 - The network is a concept that can be seen a lot in many areas of research. It is used to describe and interpret datasets in various fields such as social network, biological network, and metabolic regulation network. As a result, network diagrams appeared in various forms, and methods for visualizing the network information are being developed. In this article, we present a simple method with a weight of information data to visualize the network diagram for the three-dimensional (3D) network. The generic method of network visualization is a circular representation with many intersections. When dealing with a lot of data, the three-dimensional network graphics, which can be rotated, are easier to analyze than the two-dimensional (2D) network. The proposed algorithm focuses on visualizing three factors: the position and size of the nodes and the thickness of the edge between linked nodes. In the proposed method, an objective function is defined, which consists of two parts to locate the nodes: (i) a constraint for given distance, which is the weight of the relationship among all the data, and (ii) the mutual repulsive force among the given nodes. We apply the gradient descent method to minimize the objective function. The size of the nodes and the thickness of the edges are defined by using the weight of each node and the weight between other nodes associated with it, respectively. To demonstrate the performance of the proposed algorithm, the relationships of the characters in the two novels are visualized using 3D network diagram.

AB - The network is a concept that can be seen a lot in many areas of research. It is used to describe and interpret datasets in various fields such as social network, biological network, and metabolic regulation network. As a result, network diagrams appeared in various forms, and methods for visualizing the network information are being developed. In this article, we present a simple method with a weight of information data to visualize the network diagram for the three-dimensional (3D) network. The generic method of network visualization is a circular representation with many intersections. When dealing with a lot of data, the three-dimensional network graphics, which can be rotated, are easier to analyze than the two-dimensional (2D) network. The proposed algorithm focuses on visualizing three factors: the position and size of the nodes and the thickness of the edge between linked nodes. In the proposed method, an objective function is defined, which consists of two parts to locate the nodes: (i) a constraint for given distance, which is the weight of the relationship among all the data, and (ii) the mutual repulsive force among the given nodes. We apply the gradient descent method to minimize the objective function. The size of the nodes and the thickness of the edges are defined by using the weight of each node and the weight between other nodes associated with it, respectively. To demonstrate the performance of the proposed algorithm, the relationships of the characters in the two novels are visualized using 3D network diagram.

UR - http://www.scopus.com/inward/record.url?scp=85107573737&partnerID=8YFLogxK

U2 - 10.1155/2021/1426212

DO - 10.1155/2021/1426212

M3 - Article

AN - SCOPUS:85107573737

VL - 2021

JO - Discrete Dynamics in Nature and Society

JF - Discrete Dynamics in Nature and Society

SN - 1026-0226

M1 - 1426212

ER -