With open access gaining momentum, open reviews becomes a more persistent issue. Institutional and multidisciplinary open access repositories play a crucial role in knowledge transfer by enabling immediate accessibility to all kinds of research output. However, they still lack the quantitative assessment of the hosted research items that will facilitate the process of selecting the most relevant and distinguished content. This paper addresses this issue by proposing a computational model based on peer reviews for assessing the reputation of researchers and their research work. The model is developed as an overlay service to existing institutional or other repositories. We argue that by relying on peer opinions, we address some of the pitfalls of current approaches for calculating the reputation of authors and papers. We also introduce a much needed feature for review management, and that is calculating the reputation of reviews and reviewers.
[1]
Jordi Sabater-Mir,et al.
Simulating Research Behaviour
,
2011,
MABS.
[2]
Jordi Sabater-Mir,et al.
Propagation of Opinions in Structural Graphs
,
2010,
ECAI.
[3]
J. E. Hirsch,et al.
An index to quantify an individual's scientific research output
,
2005,
Proc. Natl. Acad. Sci. USA.
[4]
Christoph Bartneck,et al.
Detecting h-index manipulation through self-citation analysis
,
2010,
Scientometrics.
[5]
Alfonso E. Romero,et al.
Scientific impact evaluation and the effect of self-citations: Mitigating the bias by discounting the h-index
,
2012,
J. Assoc. Inf. Sci. Technol..
[6]
G. Eysenbach.
The Open Access Advantage
,
2006,
Journal of medical Internet research.
[7]
Alexander Yong,et al.
A Critique of Hirsch's Citation Index: A Combinatorial Fermi Problem
,
2014,
1402.4357.