I jumped ship from Twitter following the Musk takeover in 2022. Seeking an alternative, I joined Mastodon and didn’t look back. Since then, I’ve enjoyed many wonderful interactions and conversations; and I feel a bit sad at what Twitter turned into.

Hopefully I will soon break out of this funk of posting about either Mastodon or Twitter. But not yet! This post is to say that: I made a static archive of tweets for @quantixed and for @clathrin. There, you can read all my posts, which ended in 2022. How did I do it and why? I made the archive with this excellent tool written by Darius Kazemi.

There’s plenty of guides to getting going on Mastodon, aimed at people leaving Twitter. I just wanted to post a couple of technical points about making the switch that might be of interest to people who maintain webpages with Twitter content (feeds, embeds). Mastodon status updates (feed/timeline) Twitter provided a widget that meant that an account’s timeline could be embedded on a website.

A quick post about a puzzle called Wordle that is currently taking over the internet. It’s a mastermind-like game where the object is to guess an unknown 5-letter word. Puzzlers are encouraged to share their results after completing a puzzle. Here is an example for puzzle 192. So how do you know if your performance on today’s puzzle was any good? Why not benchmark your effort against the crowd?

Part of a series on the development of Early Career Researchers in the lab. We spent a session discussing how to create a research profile. This led to a second session on CVs. Here is an outline of what we covered. CVs We talked about different CV formats first of all. We focussed on academic CVs mainly, but we discussed the differences between academic and CVs for jobs outside academia.

This is a quick set of tips to improve your Twitter experience. YMMV on these tips. Plus I can see Twitter changing things so that they no longer work, but this advice is correct as of today.

My activity on twitter revolves around four accounts. I try to segregate what happens on each account, and there’s inevitably some overlap. But what about overlap in followers? What lucky people are following all four? How many only see the individual accounts? It’s quite easy to look at this in R. So there are 36 lucky people (or bots!) following all four accounts.