There are two problems that are coming for Mastodon of which apparently an awful lot of people are unaware. These problems are coming for Mastodon not because of anything specific to Mastodon: they come to all growing social media platforms. But for some reason most people haven't noticed them, per se.
The first problem is that scale has social effects. Most technical people know that scale has technological effects. Same thing's true on the social side, too.
For instance, consider the questions "How likely, statistically speaking, are you to run into your boss on this social media platform?" and "How likely, statistically speaking, are you to run into your mother on the social media platform?" While obviously there is wide individual variation based on personal circumstances, in general the answer to those questions is going to be a function of how widespread adoption is in one's communities.
Thing is, people behave differently on a social media platform when they think they might run into their boss there. People behave differently when they think they might run into their mother.
And it's not just bosses and mothers, right? I just use those as obvious examples that have a lot of emotional charge. People also behave differently depending on whether or not they think their next-door neighbors will be there (q.v. Nextdoor.com).
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How people behave on a social media platform turns out to be a function of whom they expect to run into – and whom they actually run into! – on that social media platform. And that turns out to be a function of how penetrant adoption is in their communities.
And a problem here is that so many assume that the behavior of users of a given social media platform is wholly attributable to the features and affordances of that social media platform!
It's very easy to mistake what are effects of being a niche or up-and- coming platform for something the platform is getting right in its design.
The example I gave about people behaving differently depending on what the likelihood is they estimate of running into certain other parties in their lives is not the only example of how scale affects how people engage with a social media platform. There are others that I know about, and probably lots I don't.
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For instance, tech people are probably aware of the phenomenon that virus writers are generally more attracted to writing viruses for platforms that have more users. This is one of the main reasons that there are (and have always been) fewer viruses written against the macOS than Windows.
You've probably never thought of it this way – mad props to the article and Omni I read a long time ago that brought this to my attention – but writing a virus is a kind of *griefing*. Like in a game. It's about fucking up other people's shit for kicks and giggles, if not for profit, and doing so at scale.
Well, griefers – people who are motivated by enjoying griefing as a pastime – are going to be more drawn to bigger platforms with more people to fuck with.
Deliberate malicious obnoxiousness and trolling varies not *linearly* with population size, but *geometrically* or worse.
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Or put another way, a social media platform can avoid a certain amount of social griefing just by being small, and therefore not worth the time of griefers who are looking for bigger fish to fry. As that platform grows, it loses that protection.
So you can't tell, not for sure, how good a platform's systems are for managing that kind of griefing until it gets big enough to really start attracting griefing at scale.
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So that's one problem: there are simply social size effects, that affect how people behave on a social media platform, so as the platform grows in adoption, how people behave on it will change. Usually not in ways that are thought of as for the better, because being a niche platform can avoid various social problems that can no longer be avoided as it grows.
The other problem I think is even more fascinating.
When a social media platform is founded, there are filter effects on who is on that platform. But as a social media platform grows, those filters – some of them – fall away.
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When I talk about filters, I mean things like the following famous examples:
* When Facebook was founded, it was only for students at universities; one could only sign up for it with a college email address. Consequently, Facebook's early userbase was almost entirely college students – with all that implies for socioeconomic class.
* When G+ was founded, it was initially opened to Google employees, and used an invite code system for rollout, such that overwhelmingly its early users were people in the same social worlds as Googlers.
* In the heyday of USENET, the vast majority of internet users, at all, were college students who are majoring in technical topics.
These social spaces, consequently, inherited (in the object oriented sense) the social norms of the demographics that initially populated them.
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Regardless of the specifics of what different platforms' initial userbases are, one of the fascinating consequence of having such filters is a higher level of social homogeneity.
I know it doesn't seem like a very high level of social homogeneity when you're in it. "What are you talking about, lady?! We have both emacs users AND vi users!"
But in a way that is largely invisible at the time to the people in it, they're in a kind of cultural bubble. They don't realize that a certain amount of social interaction is being lubricated by a common set of assumptions about how people behave and how people *should* behave.
Now they may not like those assumptions very much, they may not be very nice assumptions or ones they find are very agreeable. But they're *known*. Even if unconsciously or inchoately. And that turns out to count for a lot, in terms of reducing conflict or making it manageable.
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