The goal of rtweettree is to recursively scrape a twitter tweet and all replies, quotes, retweets and likes (that the API provides, see here) and visualize them in a network graph. The functionalities to scrape twitter data are heavily based on the excellent rtweet package. The graph network manipulation functionalities rely on the amazing tidygraph package and are visualized with ggraph.
Responsible use
rtweettree should be used in strict accordance with Twitter’s developer terms.
Installation
To get the current development version from Github (with the remotes package):
## install dev version of rtweettree from github
remotes::install_github("UrsWilke/rtweettree")Usage
In order to use rtweettree please refer to the according section of rtweet. It is probably good advice to first feel comfortable with rtweet.
Quick dive-in
First we’ll load the package.
This package can first scrape data related to a twitter status id main_status_id (The status id is the last number in the url of every tweet on twitter.) and all the replies (to replies), quotes, retweets and likes the API provides (using rtweet functions under the hood).
main_status_id <- "1438481824922181635"
rtweettree_data_scraped <- rtweettree_data(main_status_id)This results in a dataframe of rtweet data, which can then be transformed to a tidygraph::tbl_graph() object and finally visualized with ggraph. When you have loaded the rtweettree package, you can also directly use the ggplot2::autoplot() method:
ggplot2::autoplot(rtweettree_data_scraped)
A more in-depth example how to create the subtweet network graph from a tweet status_id is shown in the vignette("get_started").
Getting help
If you encounter a bug, please file an issue with a minimal reproducible example on GitHub.
