A gist demonstrating how to retrieve the people you follow, assign them to lists, and unfollow in batches

twittermgmt.R

library(rtweet) #' uses v0.7.0.9012 or higher
library(tidyverse)

## authenticate via web browser
auth_setup_default()
## people i follow
follow <- get_friends("theStephLocke")
## their user data
follow_deets <- lookup_users(follow$to_id)

## start inferring some potential lists
follow_deets %>%
  select(screen_name, last_tweet=text, description, profile_expanded_url) %>%
  mutate(data = str_detect(tolower(last_tweet), "data|sql|dataOps")) ->
  initial_categorisation

# dump to csv for manual review
write_csv(initial_categorisation, "follows.csv")

# read dataset back in after manual amends
follow_categorised<-read_csv("~/follows1.csv")

# create lists members
follow_categorised %>% 
  filter(data > 0) %>% 
  pull(screen_name) ->
  data_list

# generate lists
post_list( data_list, name = "Data folks",
           description = "People working primarily with data inc #SQLServer and #PowerBI")

# work around rate limits and flakiness of the endpoint by dumping to csv for manual c&P in tweetdeck
spit = function(x) {
  d = get(x)
  n = 1+(length(d) %/% 100)
  for (i in 1:n) {
    acc = paste0("@",d[((i-1)*100):(i*100)])
    acc = acc[!is.na(acc)]
    write_lines(acc, paste0(x,i,".csv"))
  }
}
spit(data_list)

# perform an unfollow to leave family etc in main timeline
unfollow = function(x) {
  n=50
  i=0
  while(i*n<=length(x)){
    print(i)
    to_uf=x[((i*n)+1):((i+1)*n)]
    print(to_uf)
    lapply(to_uf, post_unfollow_user)
    i=i+1
    Sys.sleep(15*60)
  }
}

# get all to unfollow
follow_categorised %>%
  filter(is.na(stay_follow)) %>%
  pull(screen_name) %>%
  unfollow()