It’s been quite interesting reading the objectives of other tweeps: what
they want to learn, make, how they want to get involved in the
community, etc. As Mike Kearney, rtweet’s maintainer, underlined, it
is excellent reading material!
On Saturday I was at my second satRday conference this year, lucky me! I got to attend satRday Cardiff which was a great experience. I gave a talk about rOpenSci onboarding system of packages, find my slidedeck here and other slidedecks at this address. A lot of R goodness!
As I did in March for satRday Cape Town, I’ll use my own tweets to summarize the event, but this time, having switched my website to blogdown I can use Hugo shortcodes as recommended by Romain François!
It’d be a bit hard for me to really write a good recap of satRday that’d do it justice! Instead, I’ll use rtweet and a bit of html hacking to storrrify it (like Storify, but in R) using my live tweets!
This prompted a reply by David Hood who later came up with R code to assign you to a Hogwarts house based on your Twitter activity!
It should be possible to assign House on the basis of Twitter analysis (among R using tweeters). Quatitatively: Original posts - opinionated - Gryffindor Replies - social - Slytherin posts links out of Twitter - homework - Ravenclaw Retweets- keeping it all working - Hufflepuff
I was thrilled to see David Hood’s sorting hat Github repo and thought it’d be the perfect occasion to answer that fascinating question: are #python users more likely to get into Slytherin than #rstats users?
Another note: I do not care about any Python vs. R fights except for Quidditch games, so go away trolls.
You’ve probably seen people posting their #Best9of2017, primarily on Instagram I’d say. I’m not an Instagram user, although I do have an account to spy on my younger sister and cousins, so I don’t even have 9 Instagram posts in total but I do love the collage people get to show off… So what about my best 9 tweets of 2017?
I don’t think rOpenSci’s Jeroen Ooms can ever top the coolness of his magick package but I have to admit other things he’s developped are not bad at all. He’s recently been working on interfaces to Google compact language detectors 2 and 3 (the latter being more experimental). I saw this cool use case and started thinking about other possible applications of the packages.
I was very sad when I realized it was too late to try and download tweets about the Eurovision song context but then I also remembered there’s this famous tennis tournament going on right now, about which people probably tweet in various languages. I don’t follow the French Open myself, but it seemed interesting to find out which languages were the most prevalent, and whether the results from the cld2 and cld3 packages are similar and whether they’re similar to the language detection results from Twitter itself.
I’ll admit I didn’t really know who Bill Nye was before yesterday. His name sounds a bit like Bill Nighy’s, that’s all I knew. But well science is all around and quite often scientists on Twitter start interesting campaigns. Remember the #actuallylivingscientists whose animals I dedicated a blog post? This time, the Twitter campaign is the #BillMeetScienceTwitter hashtag with which scientists introduce themselves to the famous science TV host Bill Nye. Here is a nice article about the movement.
Since I like surfing on Twitter trends, I decided to download a few of these tweets and to use my own R interface to the Monkeylearn machine learning API, monkeylearn (part of the rOpenSci project!), to classify the tweets in the hope of finding the most represented science fields. So, which science is all around?
This week I was impressed by this tweet where Daniel Pett, Digital Humanities Lead at the British Museum, presented a collage of Twitter profile pics of all his colleagues. He made this piece of art using R (for collecting the usernames) and Python. I’m a bit of an R fanatic (or a Python dummy…) so I decided to write a code in R only to make a collage of profile pics of Twitter #rstats users.
It’s the second time I write a post about the blog aggregator R-bloggers, probably because I’m all about R blogs now that I have one. My husband says my posts are so meta. My first post was about R blogs names, in this one I shall focus on the last 1,000 tweets from R-bloggers.
These last days a trending Twitter hashtag was “#actuallivingscientist”, whose origin can be find in this convo and whose original goal was to allow scientists to present themselves to everyone, a sort of #scicomm action. A great initiative, because we need science and we need everyone to know how it’s done, by actual human beings.
I didn’t tweet with the hashtag, but I consider myself a scientist with more or less experience in different fields – and my last post was about the scientist I married. In my timeline thanks to Auriel Fournier there were many tweets of ecologists studying animals. I’d like to say cute animals but some were carcasses… But still, it made me want to quantify which animals were the most present in the tweets. Any bet?