xxdi (version 1.2.3)

xdc_index: xdc_index

Description

This is a general function that calculates the x-index, xd-index, and xc-index for an institution using bibliometric data from an edge list. Returns the x-index or the xd-index depending on the input vector in "p1". Returns x-index when "p1" is the dataframe column containing keywords and xd-index when "p1" the dataframe column containing categories. Returns a summary table listing x-index, xd-index, and xc-index when both "p1" and "p2" are supplied. In this case, "p2" must be the higher level, i.e., categories and "p1" must be the lower level, i.e., keywords. The function is suitable for including inside loops when only one input vector is provided. However, for looping xc-index, a separate 'xc_index' function is provided which also includes an option to produce plots. Similarly, 'x_index' and 'xd_index' are standalone functions for calculating x-index and xd-index respectively as well as producing plots.

Usage

xdc_index(df, p1, p2 = NULL, id, cit, dlm1 = ";", dlm2 = ";", hg = FALSE)

Value

x-index value, and/or xd-index value, and/or xc-index value for institution.

Arguments

df

Data frame object containing bibliometric data. This data frame must have at least three columns: one for keywords/categories, one for unique IDs, and one for citation counts. Each row in the data frame should represent a document or publication.

p1

Character string specifying the name of the column in "df" that contains the first parameter of interest. Generally, this will be a column for keywords/categories. Each cell in this column may contain no keywords/categories (missing), a single keyword/category or multiple keywords/categories separated by a specified delimiter. Input the column for keywords to calculate the x-index, and the column for categories to calculate the xd-index.

p2

Character string specifying the name of the column in "df" that contains the second parameter of interest. This is an optional parameter only required when calculating xc-index. When an input is provided, it is expected that "p1" is the lower level, generally keywords, and "p2" is the higher level, generally categories. Each cell in this column may contain no categories (missing), a single category or multiple categories separated by a specified delimiter. The default is set to "NULL".

id

Character string specifying the name of the column in "df" that contains unique identifiers for each document. Each cell in this column must contain a single ID (unless missing) and not multiple IDs.

cit

Character string specifying the name of the column in "df" that contains the number of citations each document has received. Citations must be represented as integers. Each cell in this column should contain a single integer value (unless missing) representing the citation count for the corresponding document.

dlm1

Character string specifying the delimiter used in the "p1" column to separate multiple keywords/categories within a single cell. The delimiter should be consistent across the entire "p1" column. Common delimiters include ";", "/", ":", and ",". The default delimiter is set to ";".

dlm2

Character string specifying the delimiter used in the "p2" column to separate multiple categories within a single cell. The delimiter should be consistent across the entire "p2" column. Common delimiters include ";", "/", ":", and ",". The default delimiter is set to ";".

hg

Logical value indicating whether to compute Hirsch's h- and Egghe's g-indices. Default set to "FALSE".

Examples

# Create an example data frame
dat1 <- data.frame(citations = c(0, 1, 1, 2, 3, 5, 8),
                   keywords = c("a; b; c", "b; d", "c", "d", "e; g", "f", "g"),
                   id = c("abc123", "bcd234", "def345", "efg456", "fgh567", "ghi678", "hij789"),
                   categories = c("a; d; e", "b", "c", "d; g", "e", "f", "g"))
# Calculate x-index
xdc_index(df = dat1, p1 = "keywords", id = "id", cit = "citations")
# Calculate xd-index
xdc_index(df = dat1, p1 = "categories", id = "id", cit = "citations", hg = TRUE)
# Calculate x-index, xd-index, and xc-index together
xdc_index(df = dat1, p1 = "keywords", p2 = "categories", id = "id", cit = "citations", hg = TRUE)