The purpose of blueskynet is to provide tools to generate and analyze networks from Bluesky Social,
Installation
You can install the development version of blueskynet like so:
remotes::install_github("https://github.com/lassehjorthmadsen/blueskynet.git")Getting started
First, create an app password here: https://bsky.app/settings/app-passwords.
Then, set environment variable BLUESKY_APP_PASS to your app password, and another variable, BLUESKY_APP_USER, to your identifier (e.g. “lassehjorthmadsen.bsky.social”) using file.edit("~/.Renviron")
Now, you can access the core function of blueskynet:
library(blueskynet)
library(dplyr)
# Authenticate yourself
password <- Sys.getenv("BLUESKY_APP_PASS")
identifier <- Sys.getenv("BLUESKY_APP_USER")
# Then get a token and a refresh token
auth_object <- get_token(identifier, password)
token <- auth_object$accessJwt
refresh_tok <- auth_object$refreshJwt
# Establish a small net as a starting point
key_actor <- "natalieamiri.bsky.social"
keywords <- c("reporter", "journalist", "writer")
small_net <- init_net(key_actor, keywords, token)First few rows of a starting point initial network:
small_net |> head(3)
#> # A tibble: 3 × 2
#> actor_handle follows_handle
#> <chr> <chr>
#> 1 natalieamiri.bsky.social saschalobo.bsky.social
#> 2 natalieamiri.bsky.social heute.nachrichten.com.de
#> 3 natalieamiri.bsky.social iranjournal.bsky.socialWhen you’re ready, you can build a bigger net, with several supporting artifacts, like a 3d-widget, using build_network() which we won’t run here, since it can take a lot of time to build a big network.
Example application
Have a look at a network of influential scientists on Bluesky Social, generated with blueskynet here.