Tracking Cross-Disciplinary Information Use by Author Affiliation: Demonstration of a Method

Abstract

In this paper, we report the results of a bibliometric study in which we track cross-disciplinary citation behavior in the sciences. We hypothesize that cross-disciplinary citation in the sciences increased over the time period 1985–2000. Unlike most previous studies in this area, we assign discipline to a paper by its first author’s affiliation, and we hypothesize that assigning papers to disciplines based on first-author affiliation would yield results consistent with previous findings on cross-disciplinary citation rates in the sciences. Using the output of scientists in Biological Sciences, Chemistry, and Physics departments at 12 large research universities in 1985, 1990, 1995, and 2000 as our data set, we measure the cross-disciplinary citation rates of each discipline and compare our results to the findings of previous studies in this area.

An Examination of the Research Objectives of Recent Citation Analysis Studies

“…The authors were particularly interested in those citations that crossed the discipline boundaries between biology, chemistry, and physics. Ortega and Antell (2006) found that, contrary to their expectations, cross-disciplinary citations rates remained between 30 to 45 percent throughout the period. There were a few changes.…”

“…It would be interesting to know whether a longitudinal study using her techniques would show changes to these patterns and whether similar trends are present in the humanities and social sciences. Ortega and Antell (2006) also used citation analysis to examine scholars' communication patterns. They looked at the published works of researchers in the sciences and assessed how often those in one academic department cited scholars in another department.…”

Seeing the next iphone coming your way: How to anticipate converging industries

“…The distances are calculated by combining different factors which have been employed in R&D evaluation and management for a long time, such as the results of (co-)citation [45,57,58], co-authorship [8,53], co-applicant and co-word analyses [46]. Additional proxies to be used are classifications regarding keywords, subject area, journal topics and IPCs or SIC codes.…”

Employing STN Anavist to Forecast Converging Industries

“…The degree of convergence should eventually be calculated by combining different factors which have been employed in R&D evaluation and management for a long time, such as the results of (co-)citation (Meyer et al, 2008, Porter and Chubin, 1985, Rinia et al, 2002, co-authorship (Butcher andJeffrey, 2005, Ortega andAntell, 2006), co-applicant and co-word analyses (Moed, 2005). Additional proxies to be used are classifications regarding keywords, subject area, journal topics and IPCs (International Patent Classification) or SIC (Standard Industrial Classification) codes.…”