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rtweet

Collecting Twitter Data

An implementation of calls designed to collect and organize Twitter data via Twitter's REST and stream Application Program Interfaces (API), which can be found at the following URL: < https://developer.twitter.com/en/docs>. This package has been peer-reviewed by rOpenSci (v. 0.6.9).

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R client for accessing Twitter’s REST and stream APIs. Check out the rtweet package documentation website.

Responsible use

{rtweet}} should be used in strict accordance with Twitter’s developer terms.

Installation

To get the current released version from CRAN:

## install rtweet from CRAN
install.packages("rtweet")
 
## load rtweet package
library(rtweet)

To get the current development version from Github:

## install devtools package if it's not already
if (!requireNamespace("devtools", quietly = TRUE)) {
  install.packages("devtools")
}
 
## install dev version of rtweet from github
devtools::install_github("mkearney/rtweet")
 
## load rtweet package
library(rtweet)

Usage

All you need is a Twitter account and you can be up in running in minutes!

API authorization

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).

1. Create an app

  • To gain access Twitter’s APIs, first go to apps.twitter.com and create a new app by completing the form fields (note: users must enter the value for 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
  • Check yes if you agree and then click “Create your Twitter application”

2a. Authenticate via web browser (interactive)

  • Go to your app’s page at apps.twitter.com and click the tab labeled 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

    ## web browser method: create token and save it as an environment variable
    create_token(
      app = "my_twitter_research_app",
      consumer_key = "XYznzPFOFZR2a39FwWKN1Jp41",
      consumer_secret = "CtkGEWmSevZqJuKl6HHrBxbCybxI1xGLqrD5ynPd9jG0SoHZbD")

2b. Authenticate via access token

  • Go to your app’s page at apps.twitter.com and click the tab labeled Keys and Access Tokens

  • Scroll down to 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!

Package features

Search tweets

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)))

Stream tweets

Randomly sample (approximately 1%) from the live stream of all tweets.

## random sample for 30 seconds (default)
rt <- stream_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.

## stream london tweets for a week (60 secs x 60 mins * 24 hours *  7 days)
stream_tweets(
  "realdonaldtrump,trump",
  timeout = 60 * 60 * 24 * 7,
  file_name = "tweetsabouttrump.json",
  parse = FALSE
)
 
## read in the data as a tidy tbl data frame
djt <- parse_stream("tweetsabouttrump.json")

Get friends

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)
Get followers

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:

## how many total follows does cnn have?
cnn <- lookup_users("cnn")
 
## get them all (this would take a little over 5 days)
cnn_flw <- get_followers(
  "cnn", n = cnn$followers_count, retryonratelimit = TRUE
)

Get timelines

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"
  )

Get favorites

Get the 3,000 most recently favorited statuses by JK Rowling.

jkr <- get_favorites("jk_rowling", n = 3000)

Search users

Search for 1,000 users with the rstats hashtag in their profile bios.

## search for users with #rstats in their profiles
usrs <- search_users("#rstats", n = 1000)

Get trends

Discover what’s currently trending in San Francisco.

sf <- get_trends("san francisco")

Post actions

  • Posting (tweeting from R console) or reading direct messages require additional permissions
  • If you’d like to post Twitter statuses, follow or unfollow accounts, and/or read your direct messages, you’ll need to create your own Twitter app
  • To create your own Twitter app, follow the instructions in the authorization vignette on obtaining and using access tokens

Vignettes

Obtaining and using Twitter API tokens

## quick overview of rtweet functions
vignette("auth", package = "rtweet")

Quick overview of rtweet package

## quick overview of rtweet functions
vignette("intro", package = "rtweet")

Live streaming tweets data

## working with the stream
vignette("stream", package = "rtweet")

Troubleshooting common rtweet problems

## working with the stream
vignette("FAQ", package = "rtweet")

Contact

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.

News

rtweet 0.6.8

  • Users can now create read-only using the built-in rtweet client!

rtweet 0.6.7

  • lookup_coords() now requires a Google Maps API key. It will be stored for easy future use once supplied.
  • Improved documentation for authentication/token creation.
  • Various bug fixes and improvements.

rtweet 0.6.6

  • Added bearer_token() option for access to more generous rate limits.
  • Fixed issues with create_token() when using browse-based authentication method.

rtweet 0.6.5

  • Added list management functionality via post_list(), which now allows users to create and populate lists as well as delete lists on behalf of one's own Twitter account.
  • lists_memberships() and now scrolls through multiple pages of results to automate collection of larger numbers of lists.
  • Various bug fixes and improvements.

rtweet 0.6.4

  • Added new oauth method to create_token() which allows for creation of token non-interactive sessions via accepting inputs for consumer key, consumer secret (always required), oauth key, and oauth secret (optional, if supplied then non-browser sign method is used).
  • ts_*() functions now offer a tz (timezone) argument, allowing users to more easily print and plot in non-UTC time.
  • Users can now delete tweets by passing the status ID (of the desired tweet to be deleted) to the destroy_id argument in post_tweet()
  • Various bug fixes and stability improvements.

rtweet 0.6.3

  • Fixed bug in join_rtweet(), which omitted users who didn't have available tweets.
  • Various bug fixes and stability improvements.

rtweet 0.6.2

  • Added all_suggested_users(), which automates the collection of Twitter's suggested users data.
  • Various bug fixes and stability improvements.
  • Significant upgrades to save_as_csv(), including addition of new prep_as_csv() as convience function for flattening Twitter data frames.
  • Tokens have been retooled. For at least the time being, users must create a Twitter app in order to be authorized to interact with the REST and stream APIs.
  • Joined data: instead of returning users/tweets data with its complementary tweets/users data stored as an attribute, functions now return a joined data frame, consisting of the tweets-level data joined with the newest (most recent) observation for each user This means functions now return a more consistent and intuitive data object where one row is always equal to one tweet.
  • Overhauled save_as_csv() with improved flattening and ID-preserving saving methods. THe function now saves a single [joined] data set as well.
  • Fixed major bugs in get_favorites() and in several lists_*() functions.
  • Tweaked date-time aggregator internals to make time-rounding more precise.

rtweet 0.6.0

  • Introduced new API authorization method, which leverages an embedded rtweet Twitter app that is authorized locally by the user. Creating Twitter apps is non longer necessary. Users need only click "okay" to create and store their API authorization token.
  • Improved parsing and line-reading internals for stream_tweets()
  • Added stream_tweets2() function for more robust streaming method. Streams JSON files to directory and reconnects following premature disruptions.
  • Various bug fixes nad numerous documentation improvements.

rtweet 0.5.0

  • Added access to direct messages, mentions, list subscriptions, list users, list members, and list memberships
  • Various fixes to parsing, integrating tibble for output, and streamling geolocation-related functions and data.
  • Fixed issues with streaming and parsing streamed data.

rtweet 0.4.9

  • Functions get_timeline(), get_favorites(), get_friends(), and get_followers() now accept vectors of length > 1.
  • Fixed bugs related to users data and its extracter, users_data()
  • New stream parser, stream_data(), designed to parse files that cannot wholely fit into memory. stream_data() can now work in parallel as well.

rtweet 0.4.8

  • Support for additional APIs has been added--including APIs designed to return information related to lists and retweets.
  • The post_status() function has been fixed and can now be used to upload media.
  • Several adjustments have been made in response to various changes in Twitter's APIs.
  • Thanks to all the great feedback on Github, numerous bug fixes and improvements have been included as well. In general, things should become a lot more stable across functions and data structures.

rtweet 0.4.7

  • The relatively lightweight tibble package is now a package dependency.
  • Speed boosts to parsing process. It's possible to convert from json to data frames in parallel, but I'm not sure minimal gains are worth the headache. Regardless, the current version should return more data, more reliably, and faster.
  • By default, functions now return data frames (tibbles) with recursive lists (e.g., the 3rd observation of mentions_screen_name may consist of 4 screen names).
  • To revert back to the flattened/delim object, use the flatten() function. Exporting functions such as save_as_csv will apply flatten by default.
  • Three different sets of coordinate variables are now returned: coords_coords, geo_coords, and bbox_coords bounding box. The first two come in pairs of coords (a list column) and bbox_coords comes with 8 values (longX4 latX4). This should allow users to maximize returns on geo-location data.

rtweet 0.4.6

  • More efficient iterations through pages of results.
  • Added to documentation, including new package documentation domain: http://rtweet.info.
  • Improvements made in collecting and using geo data.

rtweet 0.4.5

  • Convenience function plain_tweets() added for textual analysis.
  • Overhaul of ts_plot() with improved time-aggregating method. Now a wrapper around ts_data(), deprecating ts_filter.

rtweet 0.4.4

  • Lots of query-building features added to search tweets, including ability to search by geolocation.
  • Post actions now include replying to status ID.
  • Other various bug fixes and speed improvements.

rtweet 0.4.3

  • Now returns tibbles (tibble is a recommended dependency)
  • Various bug fixes and code improvements.

rtweet 0.4.2

  • Various bug fixes
  • Integration with ggplot2 as a suggested dependency

rtweet 0.4.1

  • Fixed bugs with mutate_coords() and retryonratelimit.
  • Now returns full text of tweets exceeding 140 characters. This change was necessary due to recent changes in Twitter's API.

rtweet 0.4.0

  • CRAN release featuring major additions to documentation and support in addition to new and improved functions like ts_plot(), ts_filter() and more!

rtweet 0.3.96

  • For dev: added package builder for better versioning and more frequent updates to NEWS.md file.
  • Added new live streaming vignette as well as updated and improved tokens vignette
  • Various bug fixes and improvements to tokens, parse, and plot functions.

rtweet 0.3.93

  • All interactive/posting functions have been modified with the prefix post_. This was done to clearly distinguish write functions from retrieval functions.
  • More bug fixes and various improvements.
  • The ts_plot() function is now more robust with more adaptive characteristics for variations in the number of filters, the method of distiguishing lines, the position of the legend, and the aesthetics of the themes.
  • Added ts_filter() function which allows users to convert Twitter data into a time series-like data frame. Users may also provide filtering rules with which ts_filter() will subset the data as it converts it to multiple time series, which it then outputs as a long-form (tidy) data frame.

rtweet 0.3.92

  • search_tweets now includes retryonratelimit argument to allow for searches requesting more than 18,000 tweets. This automates what was previously possible through use of max_id.
  • Various bug fixes and improvements to parsing and pagination- assisting functions.
  • Fixed bug in encoding with stream_tweets.

rtweet 0.3.91

  • Major improvements to ts_plot including SIX different themes from which users may choose
  • More parsing fixes and misc stability improvements
  • Minor renamig of variables along with returning more variables overall

rtweet 0.3.9

  • Fixes minor problems with parse.piper function
  • More additions to plotting and data wrangling for the purpose of plotting

rtweet 0.3.8

  • Functions by default use a new faster parser that returns more variables
  • Text analysis functions provided for convenience
  • Plotting with maps
  • Tidyverse consistencies

rtweet 0.3.8

  • Fixed issue with geo tracking in stream_tweets
  • Various bug fixes and stability improvements

rtweet 0.3.7

  • Reworked ts_plot to enable different filtered time series and an aesthetic overhaul of the plot function as well.

rtweet 0.3.6

  • Added as_double argument to provide flexibility in handling id variables (as_double provides performance boost but can create problems when printing and saving, depending on format). By default functions will return IDs as character vectors.
  • Numerous improvements made to parsing and bug fixes to lookup and search functions.

rtweet 0.3.5

  • clean_tweets argument provided to allow user more control over encoding and handling of non-ascii characters.
  • Fixed issue with search_users and implemented several improvements to stream_tweets and plot_ts.

rtweet 0.3.4

  • Implemented robust methods to fetch tokens (whether set as environment variable, .httr-oauth file, or if the tokens exist in the global environment). Functions now search for variations in the labeling of tokens---i.e., if your token(s) are saved as twitter_tokens, twitter_token, tokens, or token, rtweet will find it.
  • Fixed issues with parsing tweets and users data.
  • Stability improvements to search_tweets and stream_tweeets

rtweet 0.3.3

  • Flattened recursive columns for more reliable parsing and various speed enhancements

rtweet 0.3.2

  • Added built-in, encrypted tokens
  • Fixed issues with tweets parsing and reading streams
  • Numerous speed improvements

rtweet 0.3.1

  • include_retweets arg added to search_tweets() function.
  • user_id class changed to double when parsed. double is significantly faster and consumes less space. it's also capable of handling the length of id scalars, so the only downside is truncated printing.

rtweet 0.3.0

  • New CRAN version!
  • Lots of improvements to stability and entirely new functions to play around with (see previous news updates for more info).
  • Added more documentation all round, including help features, examples, and vignette infrastructure.

rtweet 0.2.92

  • Added gzip option for stream_tweets()

rtweet 0.2.91

  • Added sample method for stream_tweets() function. By default, the streaming query argument, q, is now set to an empty string, q = "", which returns a random sample of all Tweets (pretty cool, right?).

rtweet 0.2.9

  • Added post_tweet() function. Users can now post tweets from their R console.

rtweet 0.2.8

  • Added get_favorites() function
  • Update tests
  • Exports tweets and users classes with show and plot methods

rtweet 0.2.7

  • Added screen_name variable for user mentions (in addition to user_id).

rtweet 0.2.6

  • Added lookup_statuses() function, which is the counterpart to lookup_users(). Supply a vector of status IDs and return tweet data for each status. lookup_statuses() is particularly powerful when combined with other methods designed to collect older Tweets. Early experiments with doing this all through R have turned out surprisingly well, but packaging it in a way that makes it easy to do on other machines is unlikely to happen in the short term.

  • Removed dplyr dependencies. Everyone should install and use dplyr, but for sake of parsimony, it's been removed from rtweet.

  • Continued development of S4 classes and methods. Given removal of dplyr dependencies, I've started to integrate print/show methods that will limit the number of rows (and width of columns) when printed. Given the amount of data returned in a relatively short period of time, printing entire data frames quickly becomes headache-inducing.

rtweet 0.2.5

  • S4 class and methods integration

rtweet 0.2.4

  • Added new trends functions. Find what trending locations are available with trends_available() and/or search for trends worldwide or by geogaphical location using get_trends().

  • Stability improvements including integration with Travis CI and code analysis via codecov. Token encryption method also means API testing conducted on multiple machines and systems.

rtweet 0.2.3

  • Added new search_users() function! Search for users by keyword, name, or interest and return data on the first 1000 hits.

rtweet 0.2.2

  • Output for search_tweets(), stream_tweets(), and get_timeline() now consists of tweets data and contains users data attribute.

  • Output for lookup_users() now consists of users data and contains tweets data attribute.

  • To access users data from a tweets object or vice-versa, use users_data() and tweets_data() functions on objects outputed by major rtweet retrieval functions.

  • Updated testthat tests

rtweet 0.2.1

  • Output for get_friends() and get_followers() is now a tibble of "ids". To retrieve next cursor value, use new next_cursor() function.

  • Major stability improvements via testthat tests for every major function.

rtweet 0.2.0

  • Since previous CRAN release, numerous new features and improvements to functions returning tweets, user data, and ids.

  • Search function now optimized to return more tweets per search.

  • Numerous improvements to stability, error checks, and namespace management.

rtweet 0.1.91

  • Improvements to get_friends and get_followers. Returns list with value (next_cursor) used for next page of results. When this value is 0, all results have been returned.

  • Functions get_friends and get_followers now return the list of user ids as a tibble data table, which makes the print out much cleaner.

rtweet 0.1.9

  • Improved scrolling methods such that search_tweets and get_timeline should return a lot more now

  • Added parser function to return status (tweets) AND user (users) data frames when available. As a result, the parsed output for some functions now comes as a list containing two data frames.

rtweet 0.1.8

  • Added get_timeline function that returns tweets from selected user

  • Added vignettes covering tokens and search tweets

  • Fixed issue with count argument in search and user functions

rtweet 0.1.7

  • Fixed parsing issue for return objects with omitted variables

  • Added clean_tweets convenience function for text analysis

  • More examples included in documentation.

rtweet 0.1.6

  • Added recode_error argument to get_friends function. This is especially useful for tracking networks over time.

  • Further integrated ROAuth methods/objects to increase compatibility with twitteR authorization procedures.

  • Improved token checking procedures.

rtweet 0.1.4

  • Added NEWS.md file

  • Added key features and more descriptions to README.md.

rtweet 0.1.3

  • There are now two stable parse (convert json obj to data frame) types. For user objects (e.g., output of lookup_users), there is parse_user. For tweet objects (e.g., output of search_tweets or stream_tweets), there is parse_tweets.

  • New parse functions are now exported, so they should available for use with compatible Twitter packages or user-defined API request operations.

rtweet 0.1.2

  • More parsing improvements

  • Added format_date function

  • Various stability improvements

rtweet 0.1.1

  • Improvements to parse functions

rtweet 0.1.0

  • Initial release

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.
install.packages("rtweet")

0.7.0 by Michael W. Kearney, 13 days ago

https://CRAN.R-project.org/package=rtweet

Report a bug at https://github.com/ropensci/rtweet/issues

Browse source code at https://github.com/cran/rtweet

Authors: Michael W. Kearney [aut, cre] , Andrew Heiss [rev] , Francois Briatte [rev]

Documentation:   PDF Manual  

Task views: Web Technologies and Services

MIT + file LICENSE license

Imports httr, jsonlite, magrittr, tibble, utils, progress, Rcpp, httpuv

Suggests ggplot2, knitr, magick, openssl, readr, rmarkdown, testthat, webshot, covr, igraph

Imported by VOSONDash, carbonate, needmining, rehydratoR, vosonSML.

Suggested by bdpar, graphTweets.

See at CRAN

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