We demonstrate that the disruption index (CD) recently applied to publication and patent citation networks by Park et al. (Nature, 2023) systematically decreases over time due to secular growth in research and patent production, following two distinct mechanisms unrelated to innovation – the first structural and the second behavioral. The structural explanation follows from ‘citation inflation’ (CI) (Petersen et al., Research Policy, 2018), an inextricable feature of real citation networks. One driver of CI is the ever-increasing length of reference lists, which causes the CD index to systematically decrease. The behavioral explanation reflects shifts in scholarly citation practice (e.g. self-citation) that increase the rate of triadic closure in citation networks and confounds efforts to measure disruptive innovation using CD. Combined, these two mechanisms render CD unsuitable for cross-temporal analysis, and call into question the interpretations provided by Park et al.

The enclosed supporting data accompanies the following research articles:

Alexander M. Petersen, Felber Arroyave, Fabio Pammolli (2023). The disruption index suffers from citation inflation and is confounded by shifts in scholarly citation practice. SSRN e-print: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4486421
Alexander M. Petersen, Felber Arroyave, Fabio Pammolli (2023). The disruption index is biased by citation inflation. ArXiv e-print: https://arxiv.org/abs/2306.01949

Enclosed data were generated using a synthetic citation network model developed and reported in:

Pan, R. K., Petersen, A. M., Pammolli, F. & Fortunato, S. The memory of science: Inflation, myopia, and the knowledge network. Journal of Informetrics 12, 656–678 (2018).

To summarize, provided are raw network data produced for 6 citation network scenarios. For each scenario, we include 4 synthetic networks each, for a total of 24 citation networks. Each citation network is comprised of 125270 nodes that were systematically added in cohorts, therefore representing a null model for evolving citation networks, and thereby useful for benchmarking existing and new bibliometric measures.

Enclosed code was developed using Mathematica 13 software, which should be backwards compatible with previous versions since the notebooks do not use any new functionality introduced in v13.

The disruption index suffers from citation inflation and is confounded by shifts in scholarly citation practice: synthetic citation networks for bibliometric null models

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