email list vs RSS feed vs Twitter vs periodical

About a year or two ago, I signed off my last e-mail list and rather assumed that they were a thing of the past. They were increasingly choked with announcements of self-promoting hype ‘articles’, of the “5 Amazing Things Every Great Data Scientist Does While Taking A Dump” variety. Now, to promote a workshop I’m organising, I find myself back on a couple and they’re far, far better than they were. In fact, there seem to be things on them that I hadn’t heard about by other means. It’s so hard to keep up with all the cool developments around the data world now, much harder than 10 years ago, and that’s wonderful but also time-consuming and potentially distracting from the kind of Deep Work that we are actually paid to do.

I got into Twitter instead (@robertstats), and that also served as an outlet for many little quick points I wanted to make, that were too small to constitute a blog post. And through Twitter I have learned about more people and ideas than I can even begin to count. But at the same time, that massively cut my blog output, which I regret somewhat, and intend to boost again a bit more.

The third source was other people’s blogs. It feels to me (without any data) that blogs are declining in popularity but the ones that make a genuine substantive contribution remain active. I used to get RSS feeds of new postings through Google and then later through (who host this blog), and I suppose I still do get those feeds, but never look at them. I really mean never! It’s just not immediate in the way the email is, and not compelling in the way that Twitter is. But it’s easy to post to Twitter every time you blog, and you could even set up some kind of bot to do it for you. So, I have to accept that those blogs that are not syndicated in any other way are going to get missed. It’s unfortunate but you can’t catch everything. The really good ones get tweeted by their readers if nothing else.

The crappy websites full of self-promotion still exist, and perhaps there are even more of them now, but somehow they seem to be controlled better and don’t sneak through. Maybe they fell foul of their own One Deep Learning Trick That Will Change Everything You Know About Everything, and got classified in the trash with 0.01 loss function. For my part, I only follow people who retweet with discretion. There are plenty of data people out there who seem to fire off everything that passes through their own feeds without reading it first, and although you feel you’re missing out on a great party, it’s best to just unfollow them. They won’t notice. And if you look a little deeper, you realise these people often have no Amazing Data Science to show for themselves but a whole lotta tweets; don’t forget what our former Prime Minister said on the subject.

I don’t read magazines on these sorts of subjects, except for Significance, which I am obliged to receive as an RSS (different kind of RSS there folks) fellow, and that often has something good. But I have started subscribing to the New York Times (digital). At the time it was far and away the best newspaper in the world for data journalism, dataviz and such, and I think they still have the lead but have lost some of their best team members while competitors grew into the field. Nevertheless I learn quite a lot from it as a well-curated, wide-covering international newspaper.

So, now I have two carefully chosen mailing lists, which send a daily digest, and I read them maybe once a week, taking no more than 10 seconds (literally) on each email. I get some tables of contents from journals, which are almost never interesting, but have occasional gems, so they get the same rough treatment. I read the paper but probably not as much as I should, and I am (as my homeboy Giovanni Cerulli put it) an avid consumer of Twitter, which signposts me off to all the blogs and publications and websites I might need.

I think the message here is that, as a data person, you need to think carefully about how you curate your own flow of information about new developments. It can easily take up too much of your time and disrupt your powers of concentration, but at the same time you can’t cloister yourself away or you will soon be a dinosaur. Our field is moving faster than ever and it’s a really exciting time to be working in it.


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