How Do We Engage with Other Disciplines? A Framework to Study Meaningful Interdisciplinary Discourse in Scholarly Publications

2026-01-15

arXiv.org

AI Summary

Existing approaches struggle to assess, at a fine-grained level, how citations in interdisciplinary research substantively integrate ideas from multiple fields. This work proposes a citation-purpose classification framework tailored for interdisciplinary scholarship, combining manual annotation, citation context analysis, and qualitative categorization to construct the first quantifiable system that measures both the depth and significance of citation engagement. Validated on publications at the intersection of natural language processing and computational social science, the framework not only uncovers actual patterns of interdisciplinary citation usage but also provides an actionable metric for evaluating citation quality.

Abstract

With the rising popularity of interdisciplinary work and increasing institutional incentives in this direction, there is a growing need to understand how resulting publications incorporate ideas from multiple disciplines. Existing computational approaches, such as affiliation diversity, keywords, and citation patterns, do not account for how individual citations are used to advance the citing work. Although, in line with addressing this gap, prior studies have proposed taxonomies to classify citation purpose, these frameworks are not well-suited to interdisciplinary research and do not provide quantitative measures of citation engagement quality. To address these limitations, we propose a framework for the evaluation of citation engagement in interdisciplinary Natural Language Processing (NLP) publications. Our approach introduces a citation purpose taxonomy tailored to interdisciplinary work, supported by an annotation study. We demonstrate the utility of this framework through a thorough analysis of publications at the intersection of NLP and Computational Social Science.

Problem

• interdisciplinary research
• citation engagement
• scholarly publications
• citation purpose
• computational approaches

Innovation

• interdisciplinary research
• citation purpose taxonomy
• citation engagement
• computational social science
• natural language processing