The Generation of Large Networks from Web-of-Science Data

TL;DR

This paper presents a method to generate large networks from Web-of-Science data by overcoming relational database size limitations using freeware tools, enabling more extensive network analysis.

Contribution

It introduces a novel approach to bypass relational database variable limits with txt2Pajek.exe, facilitating large-scale network generation from bibliometric data.

Findings

Enables handling larger datasets than traditional databases

Provides a practical freeware solution for network analysis

Improves capacity for bibliometric network visualization

Abstract

During the 1990s, one of us developed a series of freeware routines (http://www.leydesdorff.net/indicators) that enable the user to organize downloads from the Web-of-Science (Thomson Reuters) into a relational database, and then to export matrices for further analysis in various formats (for example, for co-author analysis). The basic format of the matrices displays each document as a case in a row that can be attributed different variables in the columns. One limitation to this approach was hitherto that relational databases typically have an upper limit for the number of variables, such as 256 or 1024. In this brief communication, we report on a way to circumvent this limitation by using txt2Pajek.exe, available as freeware from http://www.pfeffer.at/txt2pajek/.