On bibliographic networks

TL;DR

This paper presents a method to transform bibliographic data into compatible networks, enabling the derivation of new networks through multiplication, with applications demonstrated on social network data from Web of Science.

Contribution

It introduces a novel approach to network transformation and multiplication in bibliographic data, including normalization considerations and sparseness preservation.

Findings

Derived networks reveal new insights into bibliographic relationships

Normalization impacts the quality of network multiplication results

Multiplication can preserve sparseness under certain conditions

Abstract

In the paper we show that the bibliographic data can be transformed into a collection of compatible networks. Using network multiplication different interesting derived networks can be obtained. In defining them an appropriate normalization should be considered. The proposed approach can be applied also to other collections of compatible networks. We also discuss the question when the multiplication of sparse networks preserves sparseness. The proposed approaches are illustrated with analyses of collection of networks on the topic "social network" obtained from the Web of Science.