rpubmed (version 0.1)

keyword_assoc_table: Builds an association table for a character vector of search terms in a corpus. This can then e.g. be fed into igraph to generate an adjacency graph of terms Different column names can be set for the association matrix if e.g. complex regex terms are used for the keyword_list

Description

Builds an association table for a character vector of search terms in a corpus. This can then e.g. be fed into igraph to generate an adjacency graph of terms Different column names can be set for the association matrix if e.g. complex regex terms are used for the keyword_list

Usage

keyword_assoc_table(corpus, keyword_list, keyword_names = NULL, ...)

Arguments

corpus

a list of Pubmed records. e.g. as returned by fetch_in_chunks()

keyword_list

Character vector of keywords

keyword_names

NULL or Character vector of equal length to keyword_list

...

arguments to be passed to get_articles_by_terms. e.g. where = in_mesh_abstract_p

Value

matrix

Examples

## Not run: 
#      articles <- fromJSON("Test/PCD_articles.json")
#      keywords <- c("effectiveness", "treatment outcome", "comorbidity", "risk factor", "incidence")
#      k_names <- c("EFF", "TREATOUT", "COMORB", "RISK", "INCID")
#      kat <- keyword_assoc_table(corpus = articles, keyword_list = keywords, keyword_names = k_names, where = in_mesh_abstract_p)
#  ## End(Not run)