Understanding institutional collaboration networks computer science vs. psychology


Yao, Jiadi, Carr, Les and Harnad, Stevan (2013) Understanding institutional collaboration networks computer science vs. psychology At 9th International Conference on Webometrics, Informetrics and Scientometrics (WIS) & 14th COLLNET Meeting, Estonia. 15 - 17 Aug 2013.

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Description/Abstract

Institutions assume that if they are more productive (i.e., publish more papers), they will produce more high quality research. They also assume that if they collaborate more, they will be more productive. We test these causal assumptions using nearly 30 years of worldwide publication and citation data in Computer Science and Psychology. Four quality metrics, three collaboration metrics and one productivity metric were used. Spearman’s Rank Order non-parametric correlation shows that these three groups of variables are highly inter-correlated. Regression analysis was used to partial out the effect of the third variable and reveal the independent correlation between each pair of the variables.
In Computer Science, the more productive institutions publish higher quality research as measured by citation counts (including citation counts recursively weighted by the citation counts of the citing institution); the effect is the same, but not as strong, in Psychology. Higher average paper quality in both Computer Science and Psychology are more likely to be a result of greater institutional collaboration than of higher institutional productivity. The proportion of the institutional collaboration is closely linked to institutional quality and productivity. The more proportionally collaborated institutions in fact are less qualitative as well as less productive

Item Type: Conference or Workshop Item (Paper)
Venue - Dates: 9th International Conference on Webometrics, Informetrics and Scientometrics (WIS) & 14th COLLNET Meeting, Estonia, 2013-08-15 - 2013-08-17
Related URLs:
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Organisations: Web & Internet Science
ePrint ID: 358816
Date :
Date Event
15 August 2013Published
Date Deposited: 18 Oct 2013 09:08
Last Modified: 23 Feb 2017 02:21
Further Information:Google Scholar
URI: http://eprints.soton.ac.uk/id/eprint/358816

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