Ten-Year Cross-Disciplinary Comparison of the Growth of Open Access and How it Increases Research Citation Impact


Hajjem, Chawki, Harnad, Stevan and Gingras, Yves (2005) Ten-Year Cross-Disciplinary Comparison of the Growth of Open Access and How it Increases Research Citation Impact. IEEE Data Engineering Bulletin, 28, (4), 39-47.

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Description/Abstract

In 2001, Lawrence found that articles in computer science that were openly accessible (OA) on the Web were cited substantially more than those that were not. We have since replicated this effect in physics. To further test its cross-disciplinary generality, we used 1,307,038 articles published across 12 years (1992-2003) in 10 disciplines (Biology, Psychology, Sociology, Health, Political Science, Economics, Education, Law, Business, Management). We designed a robot that trawls the Web for full-texts using reference metadata (author, title, journal, etc.) and citation data from the Institute for Scientific Information (ISI) database. A preliminary signal-detection analysis of the robot's accuracy yielded a signal detectability d'=2.45 and bias = 0.52. The overall percentage of OA (relative to total OA + NOA) articles varies from 5%-16% (depending on discipline, year and country) and is slowly climbing annually (correlation r=.76, sample size N=12, probability p < 0.005). Comparing OA and NOA articles in the same journal/year, OA articles have consistently more citations, the advantage varying from 25%-250% by discipline and year. Comparing articles within six citation ranges (0, 1, 2-3, 4-7, 8-15, 16+ citations), the annual percentage of OA articles is growing significantly faster than NOA within every citation range (r > .90, N=12, p < .0005) and the effect is greater with the more highly cited articles (r = .98, N=6, p < .005). Causality cannot be determined from these data, but our prior finding of a similar pattern in physics, where percent OA is much higher (and even approaches 100% in some subfields), makes it unlikely that the OA citation advantage is merely or mostly a self-selection bias (for making only one's better articles OA). Further research will analyze the effect's timing, causal components and relation to other variables, such as, download counts, journal citation averages, article quality, co-citation measures, hub/authority ranks, growth rate, longevity, and other new impact measures generated by the growing OA database.

Item Type: Article
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Keywords: eprints, self-archiving, citation analysis, research impact, research funding, research assessment, institutional repositories, open access
Divisions: Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Web & Internet Science
ePrint ID: 261688
Date Deposited: 16 Dec 2005
Last Modified: 27 Mar 2014 20:04
Publisher: IEEE Computer Society
Further Information:Google Scholar
URI: http://eprints.soton.ac.uk/id/eprint/261688

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