I don’t think you understand anarchism.

tr*p

This is generally a censor of the word “trap”. While it obviously has several non-slur meanings, it is also used as an extremely visceral anti-trans (and in particular, anti-transfem) slur :/

The implication is that transfem people are “secretly gay men trapping straight men into being attracted to them”. It is associated with simultaneous sexualisation, homophobia, and transphobia >.<. If someone called me that IRL I would be seriously worried for my safety, as that’s often the kind of thing people would say before either raping or killing or injuring a transfem person for “”“threatening”“” their fragile sexuality, then using the trans panic defense.

The term got it’s start on 4chan, and people used it for femboy characters in anime (who are often poorly translated and may actually be trans in a lot of cases), but the kind of dehumanisation aspect of it means it very very quickly became a viscious anti-trans slur :/

those are usually the opposite of libsoc lol

It means we do not see content from them, and any posts they make or comments or similar won’t show up.

Nope! :)

Also it might be worth attaching this as a secondary standard, “DiscoveryPub” or something, to avoid scope creep.

In particular, I’ve figured out a way to specify sentiment/interests efficiently and combine it reliably over federation, and the data structures required to do that.

I’ve also provided some ideas for sensible defaults (automatic selection of instances, and accounting for instance load), with incremental enhancements to specificity for more advanced users ^.^, as well as a general search mechanism that can be derived from this - though for efficiency, it might be worth trying to develop some sort of probabalistic reverse index to avoid a linear scan, if we’re talking about discovering entities like users or groups where there may be very large numbers.

I hope that if people are interested they will boost the post onto Mastodon, which afaik is where the devs and ActivityPub standards people are, and try and get the ball rolling, because my focus is elsewhere right now, and the social aspects of developing things like this are much more difficult for me than the algorithmic and architectural parts ;3

I have made a post with some work I did to make getting into the federation without requiring users to understand it much easier here, by providing a sensible automatic way to select instances randomly but weighted :)

My idea is meant to allow for a spectrum from simply “pick an instance for me” using the weightings for an assumed “the user is interested primarily in general discussion”, to “search for an instance for me related to xyz topics as a search query”, to fine-tuned discovery ^.^

The weighting is always necessary to use because it allows instances to have more control over who they accept and avoid overloading smaller instances. But you can make the default UI very simple.

This is actually kind of a general activitypub thing. I might do that but that feels like I’d have to make it was more refined and go through some formal process, and I hate doing that kind of thing and find it quite difficult, especially since my attention is elsewhere now.

I kinda just want to put it out here so people with more attention and time and knowledge can push it forward or e.g. boost it onto mastodon. Though if it really goes nowhere I might do something? Idk ;p

Step 4 - Term Merging

Each instance has provided subject trees of what it’s community is meant to be like. Moreover, it has provided the terms it believes to refer to various concepts within their subject tree.

This step is where all those terms get merged together to then be used later via some kind of search algorithm, for the more sophisticated cases.

The steps are as follows.

• Collect all the subject trees from each instance into some way of iterating over them.
• Construct a BTree-based map of topic paths plus associated term information, merging in new values for every level from every federated server ^.^. Much more sophisticated versions of doing this efficiently are documented in the Common Interest Algorithm snippet, even if not for the terms, so just look at that :)

Step 5 - Common Interest Weighting

Apply Common Interest Weighting via the Common Interest Algorithm between the user and each possible instance.

There may be a way to use Heaps or some hierarchical datastructure to sort the instances to do this more efficiently, but as long as the implementation of the Common Interest Algorithm uses BTrees and pre-calculates lexicographically ordered maps of data it can be ensured that the cost of this kind of commonality assessment only grows with the size of the tree specified by the user and the single instance to be compared, rather than all instances (for an individual instance/user comparison ^.^).

There may also be ways to compare the user against all instances at once more efficiently that I don’t know of. But the point is, we can use the Common Interest Algorithm to assign weights for each instance/group/etc. relative to each user.

We could also use some way to convert a user search query into their Common Interest Algorithm tree weights, using the list of known terms. This is for slightly more advanced terms or people perhaps searching for communities or other groups too.

Step 6 - Elimination of Anti-Aligned Instances

Any instances/groups/communities/etc. with alignment <0 should be immediately eliminated from the list of suggested instances/groups/communities/etc. to the user.

Step 7 - Combining Sentiment Alignment Weights & Other Ranking, plus Final Selection

We already have some ranking information based on how willing and able an instance is for new users, plus we have information on how aligned each instance is with this hypothetical new user - now all a fraction from 0 to 1, as we cut out instances that have a negative alignment with the user ^.^. Then I suggest we find some simple way to join those two values together. For now, I suggest simply multiplying the alignment fraction with the weights for each instance, and then use probabalistic selection to direct the user to an instance that aligns with what they want ^.^

It may also be desirable for instances to prioritise somewhat older instances with better uptime, or more trustability (e.g. using some kind of heuristic to detect bot instances or similar), and modify the weightings based on that, or eliminate some instances ^.^

For non-instance searching or discovery, we can use the alignment ranking directly as a form of search ranking :)

Step 8 - Redirection

Redirect the user to the “final” signup page as listed in the instance metadata, along with the parameter for their desired username. Perhaps it would be worth using webfinger to make sure the username isn’t taken on any selected instance, and automatically selecting different instances from the list until you find one without the username taken already, with a warning.

If we’re talking about discoverability of communities or similar, you just put those in order of their direct sentiment alignment rank ^.^

Common Interest Algorithm

The weighting system indicates how much interest (or avoidance) an instance has for a topic as specified by the subject tree. The value of weight for each subject tree should be a value from -1 -> 1 (inclusive), and applies to the deep-most component of the tree. We’ll call this the sentiment of the instance towards that specific level of the tree.

The common interest algorithm specifies a rough way to estimate how “aligned” in sentiment a given pair of entities are using an incomplete collection of nested topic paths ^.^ and then using heuristics to fill in the “gaps” needed for direct comparison. It takes the partially specified trees - along with estimated polarisabilities - from federated instances, combines them together, then uses that to “complete” the sentiment weights specified by users and instances so they can be directly compared to determine the common interests of each to contribute to directing users to instances correct for them.

The default option should be that users are assumed to want “general sentiment/general topic/root topic” instances (i.e. with path /), and then they can specify much more refined interests using various methods, like taking search terms and using the collected known topics for them in various languages to construct a user-friendly search function based off the common interest algorithm heuristic, or allowing direct specification of interests, for more advanced users ^.^.

The full (but slightly incomplete) details of my approximate proposed Common Interest Algorithm are in this gitlab snippet, written in poorly-organised Rust code.

Tagging the Willingness for New Users

Different instances have a different level of desire (and gatekeeping) for new users.

Some don’t allow any new users at all. Others require filling out a form and waiting for approval. Many require an email or captcha, and some don’t require anything whatsoever.

Some don’t want any new users, some do accept new users but only can handle a small number, and others are free-for-all open registration.

Many users will want the ability to create communities without needing to seek approval. For defaults on the “maximum” level of “inconvenience” an instance presenting other instances should show to the user, it makes sense for an instance to use it’s own level of “inconvenience”.

nodeinfo2 (also see here for all keys) already exists to provide some basic information, but it’s not enough for this feature ;p

As such, I suggest we instead construct a property on the main server actor, for now called instance_onboarding_meta. This is an object of the form:

{
    "accepting_new_users": bool, // if this is false, no other references need be present
    "capacity_used": float (>= 0), // Must be present, represents one-minus the remaining amount of users it can take as a fraction of total estimated capacity. Alternatively, represents an approximate fraction of resource usage. If it's >1, this implies the server is over-capacity.
     "preferred_max_users": integer (>= 0), // If present, represents the approximate maximum number of users this instance wants to host. If unset, assume unlimited but perform estimates based on the fraction. 
    "signup_requirements": {
          "captcha",
          "email",
          "approval",
     }, // Must be present, a list of the signup requirements. May need more options as new authentication and validation mechanisms are added to the various Fedi servers ^.^
     "signup_uri": "https://example.com/signup/finalized" // "final" signup page, rather than one providing alternate instance suggestions. Should take e.g. a `?username=<new username>` parameter.
}

Instance Signup Redirection Algorithm

Now that a system has been proposed for giving instances to describe how much effort it takes to sign up, how much they can really take new users, and what kind of community they’re interested in, we can use this data to construct a method to split signup across the fediverse.

We’ll describe things in terms of what happens either as the list of instance values is changed while they are polled, or finally what happens when a user actually looks for an instance ^.^. Though, a lot of the ideas are also mentioned in the Common Interest Algorithm Snippet, which also at least partially discusses some other things.

Step 1 - Candidate Instance Collation

The first step is to collate information about potential candidate instances, by making requests to the endpoints described above to instances the current instance is federated with - including itself! (it might be useful to combine all the metadata into one endpoint as well, but that’s all bikeshedding):

• instance_software - the software of each instance
• instance_focus - the list of weighted subject-trees that indicate what the community is oriented around - see the algorithm snippet for efficiently merging in information from instances without having to recalculate the full weights every time, via use of BTrees/BTreeMap.
• instance_onboarding_meta - Information about how the instance accepts new users, and it’s resources to do so.

Instances shouldn’t poll this very frequently - certainly not on every attempted user signup! - and instead should cache it and poll periodically (say, every hour or so ^.^). This avoids slamming large portions of the network.

Step 2 - Software Filtering

The next step is filtering out candidate instances running different fediverse software than ourselves.

Step 3 - User Acceptance Filtering & Weighting

Our instance should then filter out instances that aren’t accepting users, and perform the following steps to assign weights to instances (may be configurable if the user is ok with accepting more effort than our instance requires - as most users are likely to use the default settings it should be cached too):

• For each instance, if it requires more things to sign up (email when we don’t need it, etc.), then remove it from the list.

  For captcha, mark that instance with a “0.5” weight multiplier rather than eliminating it, if we don’t also require captcha.

  From a user-configurability perspective, each possible requirement to signing up can either:

  • Eliminate from the list (a user doesn’t want to deal with forms) - this is the default for things required by another instance that aren’t required by ours, except captcha
  • Reduce it’s chance of selection (as in captcha) - this is the default for instances if the respective instance has captcha but the current instance doesn’t.
  • Have no effect - this is the default if we also have a requirement.

• For each instance, if it has a preferred max user count, then calculate the current approximate user count by multiplying it by the resource usage capacity.

  Then, calculate the approximate available user slots by subtracting the approximate user count from the preferred maximum. Note that this value may be negative in the case of an overloaded server.

• Find the instance with the largest preferred max user count (if none exists, then use the current server’s user count instead, though remember that if your server does have such a preferred max count, it should be in the list). If any server has an estimated total user slots consumed greater than the maximum preferred user count, use this instead.

  Then, assume that the preferred maximum for servers with no specified maximum is approximately 2x that value. Calculate the approximate available user slots of instances without an existing preferred maximum, using this estimate in combination with the resource consumption fractions.

• For any instance with available user slots <0 - that is, overloaded servers - divide those (negative) available user slots by some value such as 4.

  If any instance has a negative number of available user slots, add the most-negative number back on to every instance’s count of available user slots, so that the smallest value is zero.

  The division by 4 (or some other number) means that all overloaded servers are avoided more than they would be if we just added the most-negative value back directly.

• Assign weights to each instance depending on their proportion of available user slots compared to the total. If the instance has already been tagged by a weight (from e.g. having captcha), then multiply by that weight.

PART 3

https://fedipact.online/

You do not have to leave everything. I think lots of instances will be defederating :)

More Random Shit: https://www.abc.net.au/news/2021-04-29/facebook-whistleblower-sophie-zhang-government-manipulation/100103408

One tiny thing on the last page.

And what about after they get setup the first time?

If you don’t want to be manipulated by the algorithms that the Threads instances use to surface content, then don’t subscribe to people on Threads, it’s really not that complicated. If Meta leaves later and you find yourself desperately missing content, then guess what? That’s not Meta killing the fediverse that’s Meta having kept the fediverse alive for a while.

You do realise they can work on social groups right? It’s not just individuals, but they can propagate and push for trends even outside their direct users and communities. And if you think you’re immune to social manipulation, you’re not (insert Garfield YOU ARE NOT IMMUNE TO PROPAGANDA image here ;p)

Even if it’s harder to use, Facebook has the ability and the means to run campaigns to promote their own stuff even if it’s worse.

Federating doesn’t change that.

It makes it much much harder to do it on our network, which is the risk ^.^

Furthermore, it’s not just about that, it’s also about the fact that federating with them entwines us with their communities, and given their size it will not take long for our organisation and communities to be entirely stuck to theirs.

Oh no, we’ve recreated Reddit with millions of users and a thriving community, what a nightmare!

The nightmare is that then they can kick us around at will, buy us off, or destroy us easily. Also, their users likely would not be very aware they’re part of a federation. Did you not read the article I posted and the general concept of EEE and EEC? >.<. Furthermore, it means that their algorithms and mechanisms for pushing things become dominant and we become yet another userbase to be assimilated and farmed for manipulability by the Facebook Monolith.

Seems pretty alive to me, actually.

Then go check whatever instance you’re on three times throughout the day and do the same on Reddit and notice the distinct lack of change and movement on Lemmy/Kbin.

Lemmy/Kbin is a little less active than Reddit. This doesn’t mean it’s dead, far from it! Have you looked in new or hot?, or made sure you’re looking at the All or Subscribed feed?

Lemmy is pretty damn active.

Did you read the post?

Quesion: I don’t know if the tech limits this, but if an instance owner flips to the dark side- could past posts and content be opened up for Meta mandated data scraping? Or would any code change like that not be retroactive? Aka if we select an instance that turns bad could we be feeding the machine in the future without knowing it today?

Most of our posts are public already - that is part of how ActivityPub works. But internal data, any logs that might be kept, and a centralized repository of this data would be more accessible to Meta/FB if an instance were to be bought out.

However, this is true of essentially any entity capable of being bought, you can’t really avoid it without going full p2p and even then…

Matrix is definitely better. But that doesn’t mean Google didn’t help kill XMPP when the open protocol could absolutely have been pushed forward to fix the flaws.

Your points boil down to “Threads will be easier to use and more attractive so people will use that”, congrats, that’s the case regardless of whether or not you federate. That’s not a result of federation, that’s a result of meta having a lot of money to make good apps.

They boil down to much more than that. Even if it’s harder to use, Facebook has the ability and the means to run campaigns to promote their own stuff even if it’s worse. Furthermore, it’s not just about that, it’s also about the fact that federating with them entwines us with their communities, and given their size it will not take long for our organisation and communities to be entirely stuck to theirs.

This entire argument hinges on the idea that the Fediverse is filled with great content that Meta will just steal and present to their users when quite frankly that’s just untrue. The fediverse is still a pale imitation of Reddit that is severely lacking in content and is still likely to die from never entering the virtuous cycle required to get a social network off the ground.

Seems pretty alive to me, actually. And the risk is not just Facebook/Meta taking our content, but more us being sucked in by theirs and having their algorithms and strategies used to manipulate us and make us too dependent on their own infrastructure to sustain our own communities again, especially if they cut us off after ^.^ (the threat of which can then be used as leverage or to outright subsume large instances).