R Notebook

Creating the environment

library(tidyverse)
library(bibliometrix)
library(igraph)

Loading data

scopus_fake <- 
  read_csv("https://docs.google.com/spreadsheets/d/1USxRmsPwWFsI3kTb0wxeQn8vk4tj3onYj17OiuaRvI0/export?format=csv&gid=0")

Visualizing author co-citation networks with bibliometrix

scopus_fake_cr_au <- #  Bibliometrix creates a new columns (CR_AU) with the first author of each reference
  metaTagExtraction(M = scopus_fake, 
                    Field = "CR_AU")

author_cocitation_mat <- # Bibilometrix creates a matrix with the new column (CR_AU)
  biblioNetwork(M = data.frame(scopus_fake_cr_au), 
                analysis = "co-citation", 
                network = "authors")

bibliometrix::networkPlot(NetMatrix = author_cocitation_mat)

$graph
IGRAPH 93217de UNW- 7 9 -- 
+ attr: alpha (g/n), ylim (g/n), xlim (g/n), rescale (g/l), asp (g/n), layout (g/n),
| main (g/c), name (v/c), deg (v/n), size (v/n), label.cex (v/n), color (v/c),
| community (v/n), label.dist (v/n), frame.color (v/c), label.color (v/c), label.font
| (v/n), label (v/c), num (e/n), width (e/n), color (e/c), lty (e/n), weight (e/n),
| curved (e/l)
+ edges from 93217de (vertex names):
[1] acedo    --adams     acedo    --agarwal   acedo    --agle      acedo    --akgn     
[5] acedo    --almodovar acedo    --arregle   adams    --agle      agarwal  --akgn     
[9] almodovar--arregle  

$graph_pajek
IGRAPH 1b3473d UNW- 7 9 -- 
+ attr: name (v/c), deg (v/n), size (v/n), label.cex (v/n), id (v/c), num (e/n), weight
| (e/n)
+ edges from 1b3473d (vertex names):
[1] acedo    --adams     acedo    --agarwal   acedo    --agle      acedo    --akgn     
[5] acedo    --almodovar acedo    --arregle   adams    --agle      agarwal  --akgn     
[9] almodovar--arregle  

$cluster_obj
IGRAPH clustering multi level, groups: 3, mod: 0.15
+ groups:
  $`1`
  [1] "acedo" "adams" "agle" 
  
  $`2`
  [1] "agarwal" "akgn"   
  
  $`3`
  [1] "almodovar" "arregle"  
  

$cluster_res

$community_obj
IGRAPH clustering multi level, groups: 3, mod: 0.15
+ groups:
  $`1`
  [1] "acedo" "adams" "agle" 
  
  $`2`
  [1] "agarwal" "akgn"   
  
  $`3`
  [1] "almodovar" "arregle"  
  

$layout
            [,1]       [,2]
[1,]  0.01567692 -0.2696984
[2,] -0.11469703 -1.0000000
[3,] -1.00000000  0.3310599
[4,]  0.17455210 -0.9921749
[5,] -0.85471562  0.8850249
[6,]  0.84456709  1.0000000
[7,]  1.00000000  0.4564540

$S
NULL

$nodeDegree
    acedo     adams   agarwal      agle      akgn almodovar   arregle 
       12         4         4         4         4         4         4 

Constrasting results with igraph

co_citation_graph <- # Create a graph object
  igraph::graph_from_adjacency_matrix(author_cocitation_mat, 
                                      mode = "undirected", 
                                      weighted = TRUE) %>% 
  simplify() # Remove self citations. 

co_citation_graph %>% plot()