Returns up to 3,200 statuses posted to the timelines of each of one or more specified Twitter users.

get_timeline(user, n = 100, max_id = NULL, home = FALSE,
  parse = TRUE, check = TRUE, token = NULL, ...)

get_timelines(user, n = 100, max_id = NULL, home = FALSE,
  parse = TRUE, check = TRUE, token = NULL, ...)



Vector of user names, user IDs, or a mixture of both.


Number of tweets to return per timeline. Defaults to 100. Must be of length 1 or equal to length of user.


Character, returns results with an ID less than (that is, older than) or equal to `max_id`.


Logical, indicating whether to return a user-timeline or home-timeline. By default, home is set to FALSE, which means get_timeline returns tweets posted by the given user. To return a user's home timeline feed, that is, the tweets posted by accounts followed by a user, set the home to false.


Logical, indicating whether to return parsed (data.frames) or nested list object. By default, parse = TRUE saves users from the time [and frustrations] associated with disentangling the Twitter API return objects.


Logical indicating whether to remove check available rate limit. Ensures the request does not exceed the maximum remaining number of calls. Defaults to TRUE.


Every user should have their own Oauth (Twitter API) token. By default token = NULL this function looks for the path to a saved Twitter token via environment variables (which is what `create_token()` sets up by default during initial token creation). For instruction on how to create a Twitter token see the tokens vignette, i.e., `vignettes("auth", "rtweet")` or see ?tokens.


Further arguments passed on as parameters in API query.


A tbl data frame of tweets data with users data attribute.

See also


# NOT RUN { ## get most recent 3200 tweets posted by Donald Trump's account djt <- get_timeline("realDonaldTrump", n = 3200) ## data frame where each observation (row) is a different tweet djt ## users data for realDonaldTrump is also retrieved users_data(djt) ## retrieve timelines of mulitple users tmls <- get_timeline(c("KFC", "ConanOBrien", "NateSilver538"), n = 1000) ## it's returned as one data frame tmls ## count observations for each timeline table(tmls$screen_name) # }