#mastodonstatistics — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #mastodonstatistics, aggregated by home.social.
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Some interesting graphs on https://mastodon-analytics.com/
The first looks like good news for Mastodon. When Musk bought Twitter there was an upsurge in the number of users which tailed off but continued to rise. looking at the number of *active* users the story isn't so good. Active users fell again sharply just after the peak in registrations. Most users didn't stick with it. However the real good news is that the number of servers jumped and has remained high.
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Some interesting graphs on https://mastodon-analytics.com/
The first looks like good news for Mastodon. When Musk bought Twitter there was an upsurge in the number of users which tailed off but continued to rise. looking at the number of *active* users the story isn't so good. Active users fell again sharply just after the peak in registrations. Most users didn't stick with it. However the real good news is that the number of servers jumped and has remained high.
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Some interesting graphs on https://mastodon-analytics.com/
The first looks like good news for Mastodon. When Musk bought Twitter there was an upsurge in the number of users which tailed off but continued to rise. looking at the number of *active* users the story isn't so good. Active users fell again sharply just after the peak in registrations. Most users didn't stick with it. However the real good news is that the number of servers jumped and has remained high.
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The drawbacks of https://instances.social are known, but my guess is that the s^{-0.5} power law distribution of the number N of instances per instance size s [1] is probably insensitive to the small number of instances that are effectively <s>defederated</s> off-network.
The N \propto s^{-0.5} distribution and the deviations from that [1] don't yet seem to be well-known. #SMinusHalfDistribution
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The drawbacks of https://instances.social are known, but my guess is that the s^{-0.5} power law distribution of the number N of instances per instance size s [1] is probably insensitive to the small number of instances that are effectively <s>defederated</s> off-network.
The N \propto s^{-0.5} distribution and the deviations from that [1] don't yet seem to be well-known. #SMinusHalfDistribution
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The drawbacks of https://instances.social are known, but my guess is that the s^{-0.5} power law distribution of the number N of instances per instance size s [1] is probably insensitive to the small number of instances that are effectively <s>defederated</s> off-network.
The N \propto s^{-0.5} distribution and the deviations from that [1] don't yet seem to be well-known. #SMinusHalfDistribution
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The drawbacks of https://instances.social are known, but my guess is that the s^{-0.5} power law distribution of the number N of instances per instance size s [1] is probably insensitive to the small number of instances that are effectively <s>defederated</s> off-network.
The N \propto s^{-0.5} distribution and the deviations from that [1] don't yet seem to be well-known. #SMinusHalfDistribution
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There are *some* raw numbers at
https://codeberg.org/boud/fedistats_naive
- see the two .m octave files - these are not the numbers you're asking for, but you can copy/paste them, and the original sources are given in comments in the files.
See the following thread for the current plots and interpretation:
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There are *some* raw numbers at
https://codeberg.org/boud/fedistats_naive
- see the two .m octave files - these are not the numbers you're asking for, but you can copy/paste them, and the original sources are given in comments in the files.
See the following thread for the current plots and interpretation:
-
There are *some* raw numbers at
https://codeberg.org/boud/fedistats_naive
- see the two .m octave files - these are not the numbers you're asking for, but you can copy/paste them, and the original sources are given in comments in the files.
See the following thread for the current plots and interpretation:
-
There are *some* raw numbers at
https://codeberg.org/boud/fedistats_naive
- see the two .m octave files - these are not the numbers you're asking for, but you can copy/paste them, and the original sources are given in comments in the files.
See the following thread for the current plots and interpretation:
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5/7
(5) Distribution (total users): multiplying users by instances shows that above s = 10000, very roughly a bit less than a million users (more in one case) are in each of the eight bins from 10,000 to 1,000,000, making a bit less than 8 million users in total (in fact, about 6 million, also includes the smaller size instances). -
5/7
(5) Distribution (total users): multiplying users by instances shows that above s = 10000, very roughly a bit less than a million users (more in one case) are in each of the eight bins from 10,000 to 1,000,000, making a bit less than 8 million users in total (in fact, about 6 million, also includes the smaller size instances). -
5/7
(5) Distribution (total users): multiplying users by instances shows that above s = 10000, very roughly a bit less than a million users (more in one case) are in each of the eight bins from 10,000 to 1,000,000, making a bit less than 8 million users in total (in fact, about 6 million, also includes the smaller size instances). -
5/7
(5) Distribution (total users): multiplying users by instances shows that above s = 10000, very roughly a bit less than a million users (more in one case) are in each of the eight bins from 10,000 to 1,000,000, making a bit less than 8 million users in total (in fact, about 6 million, also includes the smaller size instances). -
3/7
(3) Distribution: a single power law of about3600 s^{-0.55} instances,
for instances each with s user accounts, provides a reasonable looking fit (Theil-Sen) [1][2]. There are a lot more small instances and a lot less big instances. This is good, and consistent with an approximate self-similar scaling.
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3/7
(3) Distribution: a single power law of about3600 s^{-0.55} instances,
for instances each with s user accounts, provides a reasonable looking fit (Theil-Sen) [1][2]. There are a lot more small instances and a lot less big instances. This is good, and consistent with an approximate self-similar scaling.
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3/7
(3) Distribution: a single power law of about3600 s^{-0.55} instances,
for instances each with s user accounts, provides a reasonable looking fit (Theil-Sen) [1][2]. There are a lot more small instances and a lot less big instances. This is good, and consistent with an approximate self-similar scaling.
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3/7
(3) Distribution: a single power law of about 3600 s^{-0.55} instances per instance with s user accounts provides a reasonable looking fit (Theil-Sen) [1][2]. There are a lot more small instances and a lot less big instances. This is good, and consistent with an approximate self-similar scaling. -
2/7
(1) Growth: The third wave since 28 Oct 2022 has stabilised to around 50k new accounts/day. Constant extrapolation * 1yr => 18M new accounts by Dec 2023. Exponential extrapolation over 3 waves => 100k daily by 1 Jan 2023. [1][2](2) Growth: Increases in instances also go in waves, each exponentially decaying. Long term exponential extrapolation (robust = Theil-Sen) over all measured waves => 10k new instances/day by 1 Jan 2023.
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2/7
(1) Growth: The third wave since 28 Oct 2022 has stabilised to around 50k new accounts/day. Constant extrapolation * 1yr => 18M new accounts by Dec 2023. Exponential extrapolation over 3 waves => 100k daily by 1 Jan 2023. [1][2](2) Growth: Increases in instances also go in waves, each exponentially decaying. Long term exponential extrapolation (robust = Theil-Sen) over all measured waves => 10k new instances/day by 1 Jan 2023.
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2/7
(1) Growth: The third wave since 28 Oct 2022 has stabilised to around 50k new accounts/day. Constant extrapolation * 1yr => 18M new accounts by Dec 2023. Exponential extrapolation over 3 waves => 100k daily by 1 Jan 2023. [1][2](2) Growth: Increases in instances also go in waves, each exponentially decaying. Long term exponential extrapolation (robust = Theil-Sen) over all measured waves => 10k new instances/day by 1 Jan 2023.
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2/7
(1) Growth: The third wave since 28 Oct 2022 has stabilised to around 50k new accounts/day. Constant extrapolation * 1yr => 18M new accounts by Dec 2023. Exponential extrapolation over 3 waves => 100k daily by 1 Jan 2023. [1][2](2) Growth: Increases in instances also go in waves, each exponentially decaying. Long term exponential extrapolation (robust = Theil-Sen) over all measured waves => 10k new instances/day by 1 Jan 2023.
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#MastodonStatistics since 28 Oct
1/7 TL;DR
* On a year's time scale, increasing to 10–20 million people is a conservative prediction; more bursts would imply higher.
* There are more instances with fewer people per instance (power law index -0.55); there's a tendency away from >30k instances and towards ~1k–30k.
* The big instances with 10k–1M people (towns/cities) would dominate by "one person one vote"; the smaller ones have lower total population (villages together have low voting power).
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#MastodonStatistics since 28 Oct
1/7 TL;DR
* On a year's time scale, increasing to 10–20 million people is a conservative prediction; more bursts would imply higher.
* There are more instances with fewer people per instance (power law index -0.55); there's a tendency away from >30k instances and towards ~1k–30k.
* The big instances with 10k–1M people (towns/cities) would dominate by "one person one vote"; the smaller ones have lower total population (villages together have low voting power).
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#MastodonStatistics since 28 Oct
1/7 TL;DR
* On a year's time scale, increasing to 10–20 million people is a conservative prediction; more bursts would imply higher.
* There are more instances with fewer people per instance (power law index -0.55); there's a tendency away from >30k instances and towards ~1k–30k.
* The big instances with 10k–1M people (towns/cities) would dominate by "one person one vote"; the smaller ones have lower total population (villages together have low voting power).
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#MastodonStatistics since 28 Oct
1/7 TL;DR
* On a year's time scale, increasing to 10–20 million people is a conservative prediction; more bursts would imply higher.
* There are more instances with fewer people per instance (power law index -0.55); there's a tendency away from 30k instances and towards ~1k–30k.
* The big instances with 10k–1M people (towns/cities) would dominate by "one person one vote"; the smaller ones have lower total population (villages together have low voting power).
