NETWORK ANALYSIS AND ITS APPLICATION IN PALEONTOLOGY — A PRELIMINARY INTRODUCTION

Network analysis (NA) is the analyzation of networks through graph theory. It is a new way of data visua- lization technique and quantitative method that can be breaking down a complex data system into its component parts and plotting them to show their interdependencies and interrelationships. There are many research cases in the fields of quantitative social science, com-puter science and machine learning. In recent years, this analytical method has attracted more and more attention in quantita-tive paleontology, especially in palaeobiogeography. In this paper, basic principles of NA and common network are briefly introduced, i.e. the adjacency matrix commonly used in co-occurrence network, and the incidence matrix involved in bipartite network. The important parameters and their definition of NA, such as average degree, graph density and modularity are also described. The two ways to realize the NA and their related tools are given, which are Gephi software and R project. After compared the procedure and results of the two ways, we found that although the network diagram can be easily generated by Gephi, and its diagram is more artistic than R, its algorithm function is limited because of deficiency of parameter settings. Furthermore, the Gephi is unable to carry out data processing before plotting, and projection of network nodes to map after plotting, while these related works can be proceeded in R project. Mostly because of flexibility of program with R language, we finally recommended use R project for network analysis. With taking the global dataset of brachiopods in the recovery period after the end Ordovician mass extinction as an example, we introduced the network analysis with R project with its package ‘igraph’ in detail. The study also tested NA using raw data compared with the revised information, and proved the importance of revision for raw data especially for small dataset. With the program we coded for processing the data and plot network graph automatically, we hope that it will be helpful for paleontologists and students who would use network analy-sis.

Project Supported:

Clc Number: