Creando ambiente de trabajo

Cargar las librerías y cargar el código.

library(tidyverse)
library(bibliometrix)
library(tidygraph)
library(igraph)
library(tidytext)
library(wordcloud)
source("verbs.R") # https://github.com/coreofscience/tidyscience/blob/main/verbs.R

Cargar los datos

scopus_df <- 
  bibliometrix::convert2df(file = "scientometrics.bib",
                           dbsource = "scopus", 
                           format = "bibtex")

Converting your scopus collection into a bibliographic dataframe

Done!


Generating affiliation field tag AU_UN from C1:  Done!

Organizar

references_df <- 
  get_references(data = scopus_df)

Análisis

Crear una red de citacion

citation_network <- 
  get_citation_network(scopus_df = scopus_df, 
                       references_df = references_df)

Limpiamos la red, de acuerdo a la propuesta de:

https://hemeroteca.unad.edu.co/index.php/nova/article/view/1735/1983

citation_network_tos <- 
  get_citation_network_tos(citation_network = citation_network)

Export data to gephi

citation_network_tos %>% 
  tidygraph::as.igraph() %>% 
  igraph::write_graph("citation.network_tos.graphml", "graphml")

Numbe de palabras del primer clúster

pal <- brewer.pal(8,"Dark2")

citation_network_tos %>% 
  activate(nodes) %>% 
  filter(subfield == 1) %>% 
  select(TI) %>% 
  as_tibble() %>% 
  unnest_tokens(output = word,
                input = TI) %>% 
  dplyr::anti_join(stop_words) %>%  
  count(word, sort = TRUE) %>% 
  filter(word == str_remove(word, pattern = "scientometrics")) %>% 
  with(wordcloud(word, 
                 n, 
                 random.order = FALSE, 
                 max.words = 50, 
                 colors=pal))

Joining, by = "word"