Scientific Reports· 2026Q1
Interdisciplinarity revealed by transitive reduction of citation networks
- 2citations
- Q1SCImago
- 2026year
Short summary
Documents retaining more citations after transitive reduction are likely interdisciplinary, while those losing many are single-field focused.
AI-generated from the title and abstract; the full text is not read.
Key points
- Transitive reduction of citation networks can identify interdisciplinary documents.
- Documents retaining more citations post-reduction are classified as multi-class (interdisciplinary).
- Documents losing a significant number of citations are classified as single-class.
- The hypothesis was supported by an artificial model and data from academic papers, court decisions, and patents.
AI-generated from the title and abstract; the full text is not read.
Abstract
Abstract We investigate the impact of transitive reduction on citation networks. Our hypothesis is that documents which lose fewer citations under transitive reduction are likely to be multi-class (our definition of interdisciplinary), while a large loss of citations suggests a document is primarily cited within a single class. We test this hypothesis by using an artificial model of a citation network and by using data on citations from three sources: academic papers, court decisions and patents. Where needed, we applied modularity-based clustering techniques on a network defined using the undirected version of the citation network to classify documents by communities. A cluster-dependent measure was then used to classify the nodes as multi-class or single-class. Our results provide strong support for our hypothesis in all four cases.
The authors' abstract, as published at the source. Scientific Reports, 2026 · DOI ↗
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Statistical and Nonlinear PhysicsPhysics and Astronomy