Most of my early R bookmarks come from R-Bloggers, at a time where this website was the best place to find tutorials that used base R and popular packages like
ggplot2. Those were my formative years, which predated things like the tidyverse.
The R user community has greatly expanded since, and following R-Bloggers has become unwieldy. I now follow the more selective and slower-paced R Weekly instead, as well as a few selected R blogs that I discovered thanks to R-Bloggers, R Weekly or Twitter, such as Bob Rudis' blog.
As of today, most of my R bookmarks come from following people on GitHub. Building a list of GitHub users with interests similar to mine has allowed me to find very specific R packages, but also R-based teaching material and non-R resources that are relevant to statistical computing and scientific research.
Last, as mentioned earlier and in another note, I check Twitter a few times per week, although I am not that much into it and have stopped automatically adding my liked tweets to my Pinboard bookmarks. As for other social media platforms, such as Facebook, Reddit or Slack, I either ignore them or use them for different purposes.
Update (February 3, 2019): this note used to display my most recent R bookmarks, but changes in cross-origin resource sharing policies now make this impossible, as Pinboard does not send an
Access-Control-Allow-Origin header in its response. The code that I use to do something similar on my academic homepage is available as a Gist.
- First published on December 14th, 2015