collabByRegionPlot: Country Collaboration Networks by Region

In massimoaria/bibliometrix: Comprehensive Science Mapping Analysis

Country Collaboration Networks by Region

Description

A function to create and plot country collaboration networks by Region

Usage

collabByRegionPlot(
  NetMatrix,
  normalize = NULL,
  n = NULL,
  degree = NULL,
  type = "auto",
  label = TRUE,
  labelsize = 1,
  label.cex = FALSE,
  label.color = FALSE,
  label.n = Inf,
  halo = FALSE,
  cluster = "walktrap",
  community.repulsion = 0,
  vos.path = NULL,
  size = 3,
  size.cex = FALSE,
  curved = FALSE,
  noloops = TRUE,
  remove.multiple = TRUE,
  remove.isolates = FALSE,
  weighted = NULL,
  edgesize = 1,
  edges.min = 0,
  alpha = 0.5,
  verbose = TRUE
)

Arguments

NetMatrix	is a country collaboration matrix obtained by the function biblioNetwork.
normalize	is a character. It can be "association", "jaccard", "inclusion","salton" or "equivalence" to obtain Association Strength, Jaccard, Inclusion, Salton or Equivalence similarity index respectively. The default is type = NULL.
n	is an integer. It indicates the number of vertices to plot.
degree	is an integer. It indicates the min frequency of a vertex. If degree is not NULL, n is ignored.
type	is a character object. It indicates the network map layout: type="auto" Automatic layout selection type="circle" Circle layout type="sphere" Sphere layout type="mds" Multidimensional Scaling layout type="fruchterman" Fruchterman-Reingold layout type="kamada" Kamada-Kawai layout
label	is logical. If TRUE vertex labels are plotted.
labelsize	is an integer. It indicates the label size in the plot. Default is labelsize=1
label.cex	is logical. If TRUE the label size of each vertex is proportional to its degree.
label.color	is logical. If TRUE, for each vertex, the label color is the same as its cluster.
label.n	is an integer. It indicates the number of vertex labels to draw.
halo	is logical. If TRUE communities are plotted using different colors. Default is halo=FALSE
cluster	is a character. It indicates the type of cluster to perform among ("none", "optimal", "louvain","leiden", "infomap","edge_betweenness","walktrap", "spinglass", "leading_eigen", "fast_greedy").
community.repulsion	is a real. It indicates the repulsion force among network communities. It is a real number between 0 and 1. Default is community.repulsion = 0.1.
vos.path	is a character indicating the full path where VOSviewer.jar is located.
size	is integer. It defines the size of each vertex. Default is size=3.
size.cex	is logical. If TRUE the size of each vertex is proportional to its degree.
curved	is a logical or a number. If TRUE edges are plotted with an optimal curvature. Default is curved=FALSE. Curved values are any numbers from 0 to 1.
noloops	is logical. If TRUE loops in the network are deleted.
remove.multiple	is logical. If TRUE multiple links are plotted using just one edge.
remove.isolates	is logical. If TRUE isolates vertices are not plotted.
weighted	This argument specifies whether to create a weighted graph from an adjacency matrix. If it is NULL then an unweighted graph is created and the elements of the adjacency matrix gives the number of edges between the vertices. If it is a character constant then for every non-zero matrix entry an edge is created and the value of the entry is added as an edge attribute named by the weighted argument. If it is TRUE then a weighted graph is created and the name of the edge attribute will be weight.
edgesize	is an integer. It indicates the network edge size.
edges.min	is an integer. It indicates the min frequency of edges between two vertices. If edge.min=0, all edges are plotted.
alpha	is a number. Legal alpha values are any numbers from 0 (transparent) to 1 (opaque). The default alpha value usually is 0.5.
verbose	is a logical. If TRUE, network will be plotted. Default is verbose = TRUE.

Value

It is a list containing the following elements:

graph		a network object of the class igraph
cluster_obj		a communities object of the package igraph
cluster_res		a data frame with main results of clustering procedure.

Examples

## Not run: 
data(management, package="bibliometrixData")

management <- metaTagExtraction(management, Field = "AU_CO")

NetMatrix <- biblioNetwork(management, analysis = "collaboration", network = "countries") 

net <- collabByRegionPlot(NetMatrix, edgesize = 4, label.cex = TRUE, labelsize=2.5, 
                          weighted = TRUE, size=0.5, size.cex=TRUE, community.repulsion = 0, 
                         verbose=FALSE)

cbind(names(net))

plot(net[[4]]$graph)

## End(Not run)

massimoaria/bibliometrix documentation built on Dec. 12, 2024, 12:47 p.m.