R client for accessing Twitter’s REST and stream APIs. Check out the rtweet package documentation website.
{rtweet}} should be used in strict accordance with Twitter’s developer terms.
To get the current released version from CRAN:
To get the current development version from Github:
All you need is a Twitter account and you can be up in running in minutes!
auth
vignette (or the API authorization section below) for instructions on obtaining access to Twitter’s APIs: https://rtweet.info/articles/auth.html.All users must be authorized to interact with Twitter’s APIs. To become authorized, follow the instructions below to (1) make a Twitter app and (2) create and save your access token (using one of the two authorization methods described below).
Callback URL
exactly as it appears below):
Name
: Name of Twitter app e.g., my_twitter_research_app
Description
: Describe use case e.g., for researching trends and behaviors on twitter
Website
: Valid website e.g., https://twitter.com/kearneymw
***Callback URL***
: http://127.0.0.1:1410
Keys and Access Tokens
Copy the Consumer Key
and Consumer Secret
values and pass them, along with the name of your app, to the create_token()
function
Keys and Access Tokens
Token Actions
and click Create my access token
Copy the Consumer Key
, Consumer Secret
, Access Token
, and Access Token Secret
values and pass them, along with the name of your app, to the create_token()
function
## access token method: create token and save it as an environment variable
create_token(
app = "my_twitter_research_app",
consumer_key = "XYznzPFOFZR2a39FwWKN1Jp41",
consumer_secret = "CtkGEWmSevZqJuKl6HHrBxbCybxI1xGLqrD5ynPd9jG0SoHZbD",
access_token = "9551451262-wK2EmA942kxZYIwa5LMKZoQA4Xc2uyIiEwu2YXL",
access_secret = "9vpiSGKg1fIPQtxc5d5ESiFlZQpfbknEN1f1m2xe5byw7")
And that’s it! You’re ready to start collecting and analyzing Twitter data! And because create_token()
automatically saves your token as an environment variable, you’ll be set for future sessions as well!
Search for up to 18,000 (non-retweeted) tweets containing the rstats hashtag.
## search for 18000 tweets using the rstats hashtag
rt <- search_tweets(
"#rstats", n = 18000, include_rts = FALSE
)
Quickly visualize frequency of tweets over time using ts_plot()
.
## plot time series of tweets
ts_plot(rt, "3 hours") +
ggplot2::theme_minimal() +
ggplot2::theme(plot.title = ggplot2::element_text(face = "bold")) +
ggplot2::labs(
x = NULL, y = NULL,
title = "Frequency of #rstats Twitter statuses from past 9 days",
subtitle = "Twitter status (tweet) counts aggregated using three-hour intervals",
caption = "\nSource: Data collected from Twitter's REST API via rtweet"
)
Twitter rate limits cap the number of search results returned to 18,000 every 15 minutes. To request more than that, simply set retryonratelimit = TRUE
and rtweet will wait for rate limit resets for you.
## search for 250,000 tweets containing the word data
rt <- search_tweets(
"data", n = 250000, retryonratelimit = TRUE
)
Search by geo-location—for example, find 10,000 tweets in the English language sent from the United States. Note: lookup_coords()
requires users have a Google API key
## search for 10,000 tweets sent from the US
rt <- search_tweets(
"lang:en", geocode = lookup_coords("usa"), n = 10000
)
## create lat/lng variables using all available tweet and profile geo-location data
rt <- lat_lng(rt)
## plot state boundaries
par(mar = c(0, 0, 0, 0))
maps::map("state", lwd = .25)
## plot lat and lng points onto state map
with(rt, points(lng, lat, pch = 20, cex = .75, col = rgb(0, .3, .7, .75)))
Randomly sample (approximately 1%) from the live stream of all tweets.
Stream all geo enabled tweets from London for 60 seconds.
## stream tweets from london for 60 seconds
rt <- stream_tweets(lookup_coords("london, uk"), timeout = 60)
Stream all tweets mentioning realDonaldTrump or Trump for a week.
Retrieve a list of all the accounts a user follows.
## get user IDs of accounts followed by CNN
cnn_fds <- get_friends("cnn")
## lookup data on those accounts
cnn_fds_data <- lookup_users(cnn_fds$user_id)
Retrieve a list of the accounts following a user.
## get user IDs of accounts following CNN
cnn_flw <- get_followers("cnn", n = 75000)
## lookup data on those accounts
cnn_flw_data <- lookup_users(cnn_flw$user_id)
Or if you really want ALL of their followers:
Get the most recent 3,200 tweets from cnn, BBCWorld, and foxnews.
## get user IDs of accounts followed by CNN
tmls <- get_timelines(c("cnn", "BBCWorld", "foxnews"), n = 3200)
## plot the frequency of tweets for each user over time
tmls %>%
dplyr::filter(created_at > "2017-10-29") %>%
dplyr::group_by(screen_name) %>%
ts_plot("days", trim = 1L) +
ggplot2::geom_point() +
ggplot2::theme_minimal() +
ggplot2::theme(
legend.title = ggplot2::element_blank(),
legend.position = "bottom",
plot.title = ggplot2::element_text(face = "bold")) +
ggplot2::labs(
x = NULL, y = NULL,
title = "Frequency of Twitter statuses posted by news organization",
subtitle = "Twitter status (tweet) counts aggregated by day from October/November 2017",
caption = "\nSource: Data collected from Twitter's REST API via rtweet"
)
Communicating with Twitter’s APIs relies on an internet connection, which can sometimes be inconsistent. With that said, if you encounter an obvious bug for which there is not already an active issue, please create a new issue with all code used (preferably a reproducible example) on Github.