library(tidyverse)
## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.0 ──
## ✓ ggplot2 3.3.3 ✓ purrr 0.3.4
## ✓ tibble 3.1.0 ✓ dplyr 1.0.5
## ✓ tidyr 1.1.3 ✓ stringr 1.4.0
## ✓ readr 1.4.0 ✓ forcats 0.5.1
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()
library(bibliometrix)
## To cite bibliometrix in publications, please use:
##
## Aria, M. & Cuccurullo, C. (2017) bibliometrix: An R-tool for comprehensive science mapping analysis, Journal of Informetrics, 11(4), pp 959-975, Elsevier.
##
##
## http:\\www.bibliometrix.org
##
##
## Help us to keep Bibliometrix free to download and use by contributing with a small donation to support our research team (https://bibliometrix.org/donate.html)
##
##
## To start with the shiny web-interface, please digit:
## biblioshiny()
wos <- convert2df(file = "wos.txt", dbsource = "wos", format = "plaintext")
##
## Converting your wos collection into a bibliographic dataframe
##
## Done!
##
##
## Generating affiliation field tag AU_UN from C1: Done!
wos %>% dim()
## [1] 283 67
wos %>% select(CR) %>% slice(1)
wos %>% select(SR) %>% slice(1)
Seleccionamos las dos columnas que necesitamos
enlaces_1 <-
wos %>%
select(SR, CR)
Crear la lista de enlaces
enlaces_2 <-
enlaces_1 %>%
separate_rows(CR, sep = ";")
write_csv(enlaces_2, "enlaces.csv")