Transitive Reduction of Citation Networks for Causal Structure Analysis

A paper by James R. Clough of Imperial College London analyzes the Transitive Reduction of citation networks. The work uses this graph-theoretic operation as a tool to reveal causal structure and highlight edges more likely to correspond to information transfer. The associated paper is available via Open Access (green) license on arXiv.

Use Cases

• Identifying key causal relationships in academic literature based on citation network structure.
• Filtering citation edges to highlight probable information transfer pathways.
• Analyzing the backbone structure of scholarly influence networks using transitive reduction.

Strengths

• Based on a formal academic paper published on arXiv.
• Focuses on a specific, well-defined graph-theoretic operation (transitive reduction).

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

paperswithcode

Collection Method

Analysis presented in an academic paper.