Interdisciplinarity as Diversity in Citation Patterns among Journals: Rao-Stirling Diversity, Relative Variety, and the Gini coefficient

TL;DR

This paper introduces a new diversity indicator, DIV, for measuring interdisciplinarity in citation patterns, addressing limitations of Rao-Stirling Diversity by separately operationalizing variety, balance, and disparity.

Contribution

The paper proposes and validates a novel diversity measure, DIV, that improves upon Rao-Stirling Diversity by independently measuring key components and applying it to large citation datasets.

Findings

DIV better distinguishes knowledge integration and diffusion.

DIV provides more consistent and meaningful diversity measurements.

The paper offers an online routine for operationalizing diversity measures.

Abstract

Questions of definition and measurement continue to constrain a consensus on the measurement of interdisciplinarity. Using Rao-Stirling (RS) Diversity produces sometimes anomalous results. We argue that these unexpected outcomes can be related to the use of "dual-concept diversity" which combines "variety" and "balance" in the definitions (ex ante). We propose to modify RS Diversity into a new indicator (DIV) which operationalizes variety, balance, and disparity independently and then combines them ex post. "Balance" can be measured using the Gini coefficient. We apply DIV to the aggregated citation patterns of 11,487 journals covered by the Journal Citation Reports 2016 of the Science Citation Index and the Social Sciences Citation Index as an empirical domain and, in more detail, to the citation patterns of 85 journals assigned to the Web-of-Science category "information science & library science" in both the cited and citing directions. We compare the results of the indicators and show that DIV provides improved results in terms of distinguishing between interdisciplinary knowledge integration (citing) versus knowledge diffusion (cited). The new diversity indicator and RS diversity measure different features. A routine for the measurement of the various operationalizations of diversity (in any data matrix) is made available online.