impact_cite: Extract additional traditional metrics from Google Scholar

In kamclean/impactr:

Extract additional traditional metrics from Google Scholar

Description

Extract additional traditional metrics from Google Scholar

Usage

impact_cite(
  data,
  var_id,
  crossref = TRUE,
  dimentions = TRUE,
  scopus = FALSE,
  oc = FALSE,
  gscholar = FALSE,
  gscholar_title_nchar = 50,
  metric = TRUE
)

Arguments

data	Dataframe containing at least two columns: publication year ("year") and id with each publication listed as a row.
var_id	String of the column name containing the publication id (accepts DOI and PMID).
crossref	Crossref database to be used for citation data (default=TRUE)
dimentions	Dimentions database to be used for citation data (default=TRUE)
scopus	Scopus database to be used for citation data (default=FALSE). Requires Scopus API.
oc	Open citations database to be used for citation data (default=FALSE due to sparse population at present).
gscholar	Google scholar database to be used for citation data (default=FALSE). Requires Google Scholar ID (and all relevent publications to be associated with this).
gscholar_title_nchar	Argument to specify how many characters the titles should be matched (default = 50). See "gscholar_invalid" output.
metric	Return common citation metrics (default = TRUE)

Value

Nested dataframe of: (1)."df": Amended dataframe with additional citation data appended (2). "time": Dataframe of citations over time (only avaiable for Scopus and google scholar). (3). "metric": output from cite_metric() (4). Unmatched recorded (only for google scholar)

kamclean/impactr documentation built on Jan. 11, 2023, 2:51 p.m.