<img src="inst/rt_logo/rt.png" width="5%", alt=""> rtweet: Collecting Twitter Data

R client for collecting data via Twitter's REST and stream API's.

Key features

• NEW (dev version on Github): Out of the box functionality! Start using rtweet the moment you install the package. Limited authorization access provided for users looking to test-drive the package before obtaining and using access tokens.

• Tweet from your R console using the post_tweet() function!

• Stream a random sample of tweets using stream_tweets(). The function default, q = "", now streams a random sample of all tweets.

• Save as CSV: If you'd like to open Twitter data in Excel or SPSS, use the save_as_csv function.

• Gather tweet data by searching past tweets search_tweets(), streaming live tweets stream_tweets(), collecting tweets from a user's timeline get_timeline(), or gathering all the tweets favorited by a user get_favorites().

• Gather user data by looking up Twitter users lookup_users(). Easily return data on thousands of users.

• Gather followers and friends data by collecting the ids of accounts following a user get_followers() or the ids of accounts followed by a user get_friends().

• Organized and easily translatable data formats. Functions return tidy data frames ready for data analysis.

Install

To get the current released version from CRAN:

install.packages("rtweet")
library(rtweet)

To get the current development version from github:

install.packages("devtools")
devtools::install_github("mkearney/rtweet")

Getting started

• Quick authorization method: To make your life easier, follow the recommended steps in obtaining and using access tokens. However, for a quick start (note: much slower in long term), you can also follow the instructions below.

• First, you'll need to create a Twitter app. For the callback field, make sure to enter: http://127.0.0.1:1410.

• Once you've created an app, record your consumer (api) and secret keys.

• Generate a token by using the create_token() function.

twitter_token <- create_token(app = "rtweet_tokens", # whatever you named app
  consumer_key = "XZgqotgOZNKlLFJqFbd8NjUtL",
  consumer_secret = "1rDnU3H3nrxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx")
# I xxx'd out the secret key, but you get the idea

• Make sure to specify twitter_token every time you use a data retrieval function, like the example below:

tw <- search_tweets("r", n = 1200, token = twitter_token, lang = "en")

• Recommended authorization method: Obtaining and using access tokens (vignette showing how to sustainably setup authorization to use Twitter's APIs).

Package description

More technical description: An implementation of calls designed to extract and organize Twitter data via Twitter's REST and stream API's. Functions formulate GET and POST requests and convert response objects to more user friendly structures, e.g., data frames or lists. Specific consideration is given to functions designed to return tweets, friends, and followers.

Contact

Email me at mkearney@ku.edu

To Do List

Data Analysis Helpers - Network analysis matrices and edge lists data structures - Text cleaner/utility functions - Data base management (SQL) integration for big data

API Functions

• get_retweeters() Retrieve users retweeting a status (in progress)
• get_list() Retrieve users in list

Vignettes

• Word cloud, textual analysis
• Network analysis featuring get_friends() and get_followers()

Documentation

• More examples, more details, and list return columns with descriptions
• Search query syntax
• Stream syntax i.e., filter vs tracking vs location
• Geo-based and date-specific queries