jep abstracts

gistfile1.txt

library(rscopus)
library(tidyverse)

issns <- c("0022-0663", "1532-6985", "1532-690X", "1532-7809", "1873-782X", "1556-6501", "8756-3894", "0959-4752", "1090-2384")
query <- str_c("ISSN(", issns, ")")

f <- function(query) {
  res <- scopus_search(query = query, max_count = 100000, count = 25, wait_time = 7)
  gen_entries_to_df(res$entries)
}

l <- map(query[-1], f)


"0022-0663" # JEP
"1532-6985" # EP
"1532-690X" # CI
"1532-7809" # JLS
"1873-782X" # CE
"1556-6501" # ETR&D
"8756-3894" # TT
"0959-4752" # LI
"1090-2384" # CEP

# abstract_retrieval(id, identifier = c("scopus_id", "eid", "doi", "pii",
#                                       "pubmed_id", "pui", "group_id"), http_end = NULL, ...)

- What are they about?
  - institutions
  - funders

- How are they related?
  - topics that co-occur
  - topic similarity
  - sociogram with authors
  - authorship in both

- How do these change over time?
  - over a five-year span