Tag: Bibliometrics

Bibliometrics: Measuring Zero-Impact

Bibliometrics aren’t just useful for analyzing who’s being cited; they are also pretty good at telling you who’s not being cited, too. Today, we’ll look at professors whose H-index (see here for a reminder of how it is calculated) is zero – that is, professors who have either never been published or (more likely) never been cited. There are three reasons why a scholar might have an H-index of zero. The first is age; younger scholars are less likely to

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Bibliometrics: Who’s the Best?

Today, we released the full version of our bibliometric paper, showing H-index averages on a discipline-by-discipline basis. You can find it here. (Keep in mind while reading it that the H-index isn’t a wholly straightforward statistic to interpret. If one discipline has an H-index of 10 and another has an H-index of five, you can’t simply say that professors in one discipline publish twice as much as the other. An H-index is just the largest number of publications for which

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Bibliometrics: Canada’s Top Ten Science Faculties

We promise fun bibliometric data, we deliver fun bibiometric data. Today: we show you how to use H-index data to identify the top ten science faculties in Canada. As we saw yesterday, science has the highest average H-index of any field; the average Canadian science professor has an H-index of 10.6. Recall that the H-index is the largest number of publications for which one also has at least the same number of citations – five papers with at least five

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Back to Bibliometrics

About two months ago, we did a series on bibliometrics (if you missed it the first time out, you can catch up here), and promised we’d be back shortly with some new results. Well, we’ll those results will be released Wednesday, and we think they’re so interesting that we’ll be spending all week telling you about them. For bibliometrics to be really useful, they need to (a) be able to capture information about both productivity and impact, (b) be easy

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Bibliometrics Part Four: Introducing the H-Index

Pretty much all systems of statistical performance measurement face a trade-off between meaningfulness and simplicity. Straightforward, easy-to-understand statistics usually don’t tell you very much because the process of simplification inevitably leaves out important aspects of reality; statistics which take complexity into account are usually clunky and difficult to explain to a lay audience. So it is with bibliometrics. We can count scholarly publications, but what if someone is just publishing in obscure journals that no one reads? We can adjust

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