“Thousands of scientists are cutting back on Twitter, seeding angst and uncertainty.” And Mastodon was the most common destination if they opened…
It’s coming up to 6 months since Musk took over Twitter, sending many of us over to Mastodon. “Scalloped growth” is what we should expect of a successful Mastodon, not exponential increase in size, says Cory Doctorow: “That’s where an outside event – a positive narrative about the new service, or a catastrophe affecting the old one – drives a surge of new users. Some of those users try the new service, decide it’s not worth it, and leave – but not all of them. Each event triggers a high tide of new signups, but the low tide that follows is still higher than the old level. Surge after surge, the number of users steadily builds, despite the normal ebb and flow.”
As Mastodon attracts new users, network effects can kick in, he wrote: “The people who stay on Mastodon make it a busier, more exciting place, which means that the next surge will find an even higher equilibrium, as users who try Mastodon find more fully acclimated users who can hold their hands as they get settled in, and also provide the vibrant community that presents a good reason for doing so.”
Does Mastodon’s growth fit that pattern? If you pull back and look at Mastodon usage over time, then yes. Major surges are sporadic, but activity does end up at a higher level after growth spurts subside.
A caveat before we look at data: How big Mastodon is at any given point depends on how broadly you cast the net across the “Mastodon” network – there are some very large nodes, plus thousands of small ones. As well as different selections of what’s counted, different constellations of Mastodon-based websites allow their user numbers to be scooped up by various collectors.
The end result is that no source can tell us exactly how big it all is, and data sources vary, sometimes quite dramatically. For example, some don’t include Japan’s Pawoo.net in their scope which has a big impact on totals – as I was writing, there were over 856,000 users in that one node. So think of the graphs I’m including as roughly indicative of broad patterns, with a lot of inherent uncertainty. (An overview of data sources, including some data from each before and after the takeover so you can compare their reach, are below this post.)
I didn’t have access to a reliable source of user data since the start of Mastodon. So my first chart draws on 2 sources that seem to me to be casting a reasonably similar net across Mastodon. Even with a couple of major gaps in time – including important events like the 2018 surge around #DeleteFacebook – the pattern of growth kicked into higher gear by sporadic surges is clear. (Click on the image or here for the underlying data.)
The number of monthly active users is a good way to get a handle on the post-Twitter-takeover pattern of a decline after a surge, leaving behind a busier and more exciting community. That’s how many people with accounts have logged in at least once in the previous month. For that, let’s look at the “official” Mastodon data. The elevated level of Mastodon community activity after the post-Musk surges has been ebbing this year, though it has settled to a plateau in April. (Click on the image or here for the underlying data. Note there were 2 days of missing data.)
There was a long slow slump in overall activity, but the active user rate is still over 3 times as high as it was before the takeover. Another way to look at it: The rate of monthly active users was about 10% of all Mastodon accounts before the takeover. It’s 18% now. Within that broad picture, there’s huge variation from community to community.
There are communities that have reached critical mass – if your interest is say, computer science or tech and programming, a lot of your crowd is on Mastodon. That doesn’t seem to be common, though. Some of my areas of interest are well-covered and thriving, but others aren’t. Back in November, deep in the cluster of post-Musk Mastodon Migration surges, I wrote about Science Twitter having formed an exciting community there, even if it still wasn’t clear how many would stay. That’s subsided, for now at least. But the quality (and quantity) of interaction I’m experiencing is great, without Twitter’s stress. So I’m not going back.
Much of Science Twitter returned there, and a lot of the science and science journalism community never really left, though activity has slumped. I haven’t tried to track it, but I’m sure many have reduced their social media use, or spend more time elsewhere. Some are trying out every new “Twitter alternative” that appears, still looking to re-capture Twitter’s heyday. Mike Masnick has just written a terrific article on the options in the post-Twitter landscape.
I’m not looking for an alternative to Mastodon, for now at least. And I’m not really expecting there to be a “new Twitter”. Journalism professor Jeff Jarvis was quoted in an interesting new article on the current turmoil in online news and social media, by Bobby Allyn. I think Jarvis captures this moment, arguing that big Web companies are losing power and will continue to, and we’ll keep shifting from large social media platforms to smaller communities. He pointed out that it was 150 years after Gutenberg before newspapers emerged, and what comes next could take time to emerge.
In the meantime, there’s a variety of alternatives: “We don’t need to operate at the scale of mass media, or the scale of Silicon Valley and venture capital,” Jarvis said, “… we can get back to a human scale of small.”
Interested in Mastodon? Check out my Shortcuts to Giving Mastodon a Try.
Disclosures: I joined Twitter in October 2010. My now-inactive Twitter account had just under 10,000 followers before the Covid-19 pandemic, and peaked a few hundred above 32,000. They were down to 30,000 as of writing. I joined Mastodon on October 31, 2022, and currently have over 4,600 followers there. (PLOS is on Mastodon, as are PLOS journals.)
The cartoon at the top of this post is my own (CC BY-NC-ND license). (More cartoons at Statistically Funny.)The image in the thumbnail at the foot of the post is public domain. It includes a data chart of mine, and a public domain Mastodon mascot via Wikimedia Commons.
Mastodon and Fediverse data sources
I wrote a post last year grappling with Mastodon statistics and the various claims about how big Mastodon was. The nub of it: How big Mastodon is at any given point depends on how broadly you define “Mastodon”, and there’s a lot of variation depending on which source you look at. I included 4 sources of usage data in that post. For this one, I’ve used 6, one of which was a bot that stopped in 2018. The 5 data sources that continue are in the table below.
I’ve only been discussing data on Mastodon. But Mastodon is part of a broader network called the Fediverse (short for federated universe). The services can, and mostly do, interconnect, so growth in other parts of the Fediverse is a vital part of the picture. Mastodon isn’t the only microblogging service within the Fediverse, either, although it’s overwhelmingly the largest. It makes no practical difference, though, if I want to follow someone from a Mastodon home or Calckey, for example. So where available, I’ve included Fediverse data below.
Before = October 2022 where monthly data; October 27 when daily (before Musk’s takeover of Twitter).
After = April 2023 when monthly data; April 28 when daily.
|1||Official Mastodon API|
(See charts using this API data, by Tobia Alberti and this bot on Mastodon, Mastodon daily active users)
(Posted each day)
|3||* Fediverse Observer:|
(Poduptime on gitlab) (API)
(gallizoltan on github)
Data source: instances.social (API)