predict_h_index {scholar}

Predicts the h-index for a researcher

Description

Predicts the h-index for a researcher each year for ten years into the future using Acuna et al's method (see source). The model was fit to data from neuroscience researchers with an h-index greater than 5 and between 5 to 12 years since publishing their first article. So naturally if this isn't you, then the results should be taken with a large pinch of salt.

Usage

predict_h_index(id, journals)

Arguments

id

a character string giving the Google Scholar ID

journals

optional character vector of top journals. See get_num_top_journals for more details.

Details

Since the model is calibrated to neuroscience researchers, it is entirely possible that very strange (e.g. negative) h-indices will be predicted if you are a researcher in another field. A warning will be displayed if the sequence of predicted h-indices contains a negative value or is non-increasing.

Value

a data frame giving predicted h-index values in future

Note

A scientist has an h-index of n if he or she publishes n papers with at least n citations each. Values returned are fractional so it's up to your own vanity whether you want to round up or down.

Source

DE Acuna, S Allesina, KP Kording (2012) Future impact: Predicting scientific success. Nature 489, 201-202. doi:10.1038/489201a. Thanks to DE Acuna for providing the full regression coefficients for each year ahead prediction.

Examples

  ## Predict h-index of original method author
## Not run: 
  id <- "DO5oG40AAAAJ"
  df <- predict_h_index(id)

## End(Not run)