characterize_kw: Characterize bibliometric corpus with keywords.
In MaximeRivest/scimeetr: Scientometrics Meet R

Description Usage Arguments Value See Also Examples

characterize_kw calculates several keyword metrics from a scimeetr object. The results are returned in a list of data frame. The metrics in the table are: keywords frequency, keywords relative frequency, and keywords relevance.

1	characterize_kw(scimeetr_data, lambda = 0.4)

`scimeetr_data`	An object of class scimeetr.
`lambda`	A number from 0 to 1. If 0 the relevance score would be equal to the relative frequency. If 1 for the relevance score would be equal to the frequency.

A list of dataframe. The list length matchs the number of communities that the scimeetr object contains.

characterize_jo for journal characterization, characterize_ti for title-word characterization, characterize_ab for abstract-word characterization, characterize_au for author characterization, characterize_un for university characterization, characterize_co for country characterization

# Example with an object of class scimeetr (see import_wos_files() or 
# import_scopus_files()) already in the workspace
keywords_list <- characterize_kw(scimeetr_list)
# Since this example shows how to load WOS from your system we need to run 
# the following line to find the path to the exemple file
fpath <- system.file("extdata", package="scimeetr") 
fpath <- paste(fpath, "/wos_folder/", sep = "") 
# Then we can run the actual example
example_scimeetr_object <- import_wos_files(files_directory = fpath)
characterize_kw(example_scimeetr_object)