Review Paper Publication and Citation Trends with GenAI Signal Analysis

A dataset supporting research into the changing status of academic review papers. It likely contains metrics on publication volume, citation rates, and evidence of Generative AI usage across a wide range of fields. The dataset was created by Barry Smyth and last updated in April 2026.

Use Cases

• Analyzing trends in review paper publication volume based on raw numbers and proportion of output.
• Quantifying the 'citation dividend' for review papers and modeling its decline over time.
• Investigating the prevalence of Generative AI usage in paper writing, comparing signals in review versus primary research papers.

Strengths

• Dataset size is 1.5 GB, indicating a medium-scale data collection.
• Published under a permissive CC-BY-4.0 license, facilitating reuse and sharing.
• Last updated date of 2026-04-23 is provided for recency assessment.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

Barry Smyth via figshare

Collection Method

Analysis of academic publishing data across a wide range of fields, as described in the associated paper.

Time Range

Recent years up to 2026, as indicated by the analysis of GenAI impact.

Freshness

Last updated 2026-04-23 14:09:34.

Geography

Global, as the study covers a wide range of fields without specified geographic restriction.