I've started three thematic microblogs you may be interested in.
They are all link and quote microblogs that reflect side interests related to my work but that I don't want to force onto all of my twenty-five readers. My main microblog is focused on work related matters, projects etc. and I plan on keeping it that way. Original posts may happen, but are not planned.

The first microblog is The Ascetic Programmer, @asceticprogrammer. It's about exercising various forms of restraint when writing programs to achieve a higher quality. The first batch of links is all about conciseness of programs, how short programs are better. That's probably the main unifying theme and surely not an idea I originally conceived, but I enjoy connecting different points of view and anecdotes from great people in computing and I also hope to add more code snippets that exemplify conciseness at its best. The different quotes relate conciseness with several positive program properties, like correctness, low cost and even beauty. There are also other forms of restraint like not using side effects, keeping interfaces small, keeping functions, modules or objects small and focused. The idea if one can't shrink the total program size, having many small parts loosely coupled is better than one big plate of spaghetti code. I hope to add links about these and other forms of restraint in programming in the future.

The second microblog, Science in Crisis, @sciencecrisis, is about what I regard as a crisis in the scientific method. This is a critique from the inside (I published my fair share of papers and I am no creationist or global warming denier type). The crux of the matter is that results don't replicate. It's not a few bad apples. Replication is a crucial requirement of science. It ensures results are not subjective and that they stand the test of time. Sloppy statistical methods, correlation taken for causation, publication bias, selective suppression of results, economic pressures, there's a lot going on. I don't think there is a simple solution, but practitioners and observers alike need to be aware of the problem and be part of a debate about how to tackle it.

The third is Data Science Matters, @datascimatters. It is a reaction to the famous quote "The best minds of my generation are thinking about how to make people click ads, that sucks". Is Data Science really the science of ads? Or the science of Farmville addiction? I hope not, so whenever I hear of an application that matters, I will post about it there. I know that the powerful "work on stuff that matters" call has not been invented here and I acknowledge this is a variation on that theme. But — call me old fashioned — I do not find "creating more value than you capture" so uplifting, nor I can stand trivializations of the slogan according to which it means that you should only endeavor to create the next technology behemoth. To me Data Science matters when it applies to the pressing issues of our time, climate, health, poverty,  resources, human rights, environment, that kind of stuff that matters.

All three microblogs are open to contributions, under my editorial control. I hope you enjoy them.