Google Scholar Metrics

Google continues to offer new tools to estimate impact of scientific publications. Given the sheer volume of the indexed publications, it could be expected that the results are quite meaningful (as always, any numerology about publications, e.g., total number of citations, h-index, impact factor and so on, should be taken with a serious grain of salt). Now Google provides information on the top hundred scientific journals ordered by 5-year h-index. I assume, more to follow.

Here is the Google Metrics help page.

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About Artem Novozhilov

I am an applied mathematician interested in studying various evolutionary processes by means of mathematical models. More on my professional activities can be found on my page https://www.ndsu.edu/pubweb/~novozhil/
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3 Responses to Google Scholar Metrics

  1. Yuri Wolf says:

    I think it’s not a good metric. Imagine that publications are picked prom a single distribution of (future) citation values and assigned to journals randomly. h5 index is determined by the sampled right tail of this distribution. Journals that publish more have a clear advantage. Compare positions of PLOS One and PLOS Biology or English and Dutch journals to see this effect in action.

    Good impact metric should address the question “what sort of quality should I expect from a paper published in journal”. IMHO, ISI impact factor answers this better than Google h5.

    • Absolutely, what Google offers is not a good metric (look simply at arXiv atop of Cell). About the ISI impact factor, I just would like to cite the following: “When a measure becomes a target, it ceases to be a good measure” (Goodhart’s law) :). What I actually like about Google is that they continue to add various bibliometric tools, which are free to use, including quite useful Google Scholar Citations, which is better even than ISI because the authors can keep track of their own papers (btw, maybe you can join? ). I am sure they will add some statistics on various journals soon.

      • Yuri Wolf says:

        “When a measure becomes a target, it ceases to be a good measure” (Goodhart’s law) – brilliant!

        Incidentally, I find h5 a reasonable measure of the scientific output of a person or a small group – entities that face the quantity-quality trade-off. Publishers don’t.

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