Revealing Comparative Advantages in the Backbone of Science

TL;DR

This paper introduces a novel approach using the Revealed Comparative Advantage (RCA) index to map and analyze the global distribution and relationships of scientific knowledge across countries, addressing bias issues in traditional measures.

Contribution

It applies RCA to scientometric data to create unbiased, comparative science maps of knowledge areas and countries, offering a new visualization method.

Findings

RCA effectively reduces bias in country-based scientific measures.

Science maps of 27 knowledge areas and 237 countries are successfully generated.

The approach is feasible for global scientific production analysis.

Abstract

Mapping Science across countries is a challenging task in the field of Scientometrics. A number of efforts trying to cope with this task has been discussed in the state of the art, addressing this challenge by processing collections of scientific digital libraries and visualizing author-based measures (for instance, the h-index) or document-based measures (for instance, the averaged number of citations per document). A major drawback of these approaches is related to the presence of bias. The bigger the country, the higher the measure value. We explore the use of an econometric index to tackle this limitation, known as the Revealed Comparative Advantage measure (RCA). Using RCA, the diversity and ubiquity of each field of knowledge is mapped across countries. Then, a RCA-based proximity function is explored to visualize citation and h-index ubiquity. Science maps relating 27 knowledge areas and 237 countries are introduced using data crawled from Scimago that ranges from 1996 to 2011. Our results shows that the proposal is feasible and can be extended to ellaborate a global scientific production characterization.