Does the Leiden Manifesto need a "Skewness Principle"?

[Ismael Rafols]

Dear all,

In the ISSI conference in Istanbul next week there will be a special
session on the Leiden Manifesto (http://leidenmanifesto.org).

This will be on *July 2nd, Thursday, 10:00-11:30 at Albert Long Hal*l.

Diana Hicks, the leading author, will present the principles of Leiden
Manifesto. Paul Wouters will chair first a panel with members from diverse
institutions, and second, a discussion with all the audience.

In this session, we hope there will be space for debating the current
principles, their implementation, critiques and potential improvements such
the one proposed by Andreas in the previous e-mail.

We are looking forward to your active participation so that, as a
professional community, we collectively succeed in providing the best
advice about the usages of scientometrics.

Best regards,

Ismael Rafols
Ingenio (CSIC-UPV, València; SPRU, Sussex)


2015-06-24 13:11 GMT+02:00 Andreas Strotmann <andreas.strotmann at gmail.com>:

> Adminstrative info for SIGMETRICS (for example unsubscribe):
> http://web.utk.edu/~gwhitney/sigmetrics.html



> Does the Leiden Manifesto need to add a "skewness" principle, i.e., an
> admonition to always take into account that bibliometric data is likely to
> suffer from skewed error distributions, including a reminder that for
> typical skewed error distributions, your usual network statistics are
> likely way off the truth unless the data used for analysis is of excellent
> quality, both wrt. completeness and wrt. correctness?
>
> Slides for a presentation in which we argue for this are now online on
> Researchgate (researchgate.net/publication/279162430). Since this
> presentation was mainly meant to ignite discussion, but the ISSI conference
> program does not actually reserve time for discussion after ignite
> presentations, I would like to offer this topic up for discussion on this
> mailing list already.
>
> It is true that most people in our field are aware of the problem and its
> solutions to some extent, but fact is that I see publications that violate
> the proposed principle all too frequently. Admittedly, in-depth research
> asking just how good network data needs to be so you can trust results from
> analyzing it has only very recently begun, but the references that I
> collected in these slides seem to indicate that the problem (while still
> manageable) has been severely underestimated.
>
> Hoping for a lively discussion,
>
>  -- Andreas
>
>
>
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