I have many tibbles similar to this:
dftest_tw <- structure(list(text = c(\"RT @BitMEXdotcom: A new high: US$500M turnover in the last 24 hours, over 80% of i
We can use tidyverse options. Get the value of multiple string objects with mget, then with map2 from purrr, create the new column 'Twitter.name in each dataset of the list with corresponding string element of 'myUserList`
library(tidyverse)
lst <- mget(myUserList) %>%
map2(myUserList, ~mutate(.data = .x, Twitter.name = .y))
If we need to modify the objects in the global environment, use list2env
list2env(lst, envir = .GlobalEnv)