impact_auth_network: Create a dataframe for network analysis of co-authorship

In kamclean/impactr:

Create a dataframe for network analysis of co-authorship

Description

Create a dataframe for network analysis of co-authorship

Usage

impact_auth_network(
  df,
  author = "author_list",
  id = "pubmed",
  auth_interest = "",
  initial_right = TRUE,
  initial_num = 1,
  edge_min = 1
)

Arguments

df	Dataframe with 2 mandatory columns (1) "id": A vector of unique paper IDs (e.g. DOI / PMID) (2) "author": A vector of strings of all authors (format must be last name + initials)
author	Name of the "author" variable in the dataframe (default="author_list")
id	Name of the "id" variable in the dataframe (default="pubmed")
auth_interest	= List of authors of interest (will exclude all vertices *not* involving these authors)
initial_right	= Are the initials to the right of the last name? (default = TRUE)
edge_min	= The minimum number of edges (weight) desired (default = 1)
initial_n	= Number of initials to match authors on (default = 1).

Value

Nested dataframe of: (1) Nodes (2) Vertices for network analysis

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