Comparing Retrieval Strategies to Capture Interdisciplinary Scientific Research: A Bibliometric Evaluation of the Integration of Neuroscience and Computer Science

TL;DR

This study compares four retrieval strategies to effectively identify interdisciplinary research between neuroscience and computer science, highlighting the superior performance of reference-based methods for building interdisciplinary corpora.

Contribution

The paper introduces and evaluates four novel retrieval strategies for constructing interdisciplinary research datasets, emphasizing the effectiveness of reference-based approaches.

Findings

Reference-based strategy outperforms keyword-based methods in retrieval quality.

Reference-based approach yields higher pseudorecall and F1 scores.

Methodology applicable to various interdisciplinary research domains.

Abstract

Interdisciplinary scientific research is increasingly important in knowledge production, funding policies, and academic discussions on scholarly communication. While many studies focus on interdisciplinary corpora defined a priori -- usually through keyword-based searches within assumed interdisciplinary domains -- few explore interdisciplinarity as an emergent intersection between two distinct fields. Thus, methodological proposals for building databases at the intersection of two fields of knowledge are scarce. The goal of this article is to develop and compare different strategies for defining an interdisciplinary corpus between two bodies of knowledge. As a case study, we focus on the intersection between neuroscience and computer science. To this end, we develop and compare four retrieval strategies, two of them based on keywords and two based on citation and reference patterns. Our results show that the reference-based strategy provides better retrieval, pseudorecall, and F1. While we focus on comparing strategies for the study of the intersection between the fields of neuroscience and computer science, this methodological reflection is applicable to a wide range of interdisciplinary domains.