Rank your own sample of journals

29 12 2020

If you follow my blog regularly, you’ll know that around the middle of each year I publish a list of journals in conservation and ecology ranked according to a multi-index algorithm we developed back in 2016. The rank I release coincides with the release of the Web of Knowledge Impact Factors, various Scopus indices, and the Google Scholar journal ranks.

The reasons we developed a multi-index rank are many (summarised here), but they essentially boil down to the following rationale:

(i) No single existing index is without its own faults; (ii) ranks are only really meaningful when expressed on a relative scale; and (iii) different disciplines have wildly different index values, so generally disciplines aren’t easily compared.

That’s why I made the R code available to anyone wishing to reproduce their own ranked sample of journals. However, given that implementing the R code takes a bit of know-how, I decided to apply my new-found addiction to R Shiny to create (yet another) app.

Welcome to the JournalRankShiny app.

This new app takes a pre-defined list of journals and the required indices, and does the resampled ranking for you based on a few input parameters that you can set. It also provides a few nice graphs for the ranks (and their uncertainties), as well as a plot showing the relationship between the resulting ranks and the journal’s Impact Factor (for comparison).

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