#ontology — Public Fediverse posts

talking metaphysical and mythical... what if this (PHYSICAL HEALTH/SURVIVAL OF WORLD/HUMANS) is what that (ETERNAL LIFE) meant? Perhaps not about individuals at all, or any post-body, ghost experience of eternity, but regarding eternity versus extinction for the #world #humankind #heaven #hell #doomed af #poetry #ontology
https://rant.li/atmercurialatrant-li/everlasting-life-of-the-world

Just published: a systematic comparison of Graham Harman's Object-Oriented Ontology (OOO) with my own Conference of Difference (CoD) model.

Alexander Stepanov said Object-Oriented Programming (OOP) obscures process behind static objects. Does the same critique apply to Harman's OOO?

Does objectification hide the relational flow that actually constitutes being?

👉 https://www.johnmackay.net/cod-thesis-c0360-graham-harman.htm
#Ontology #Philosophy

The #Paradigm Shift – Renovating the Dualistic Structure of Science

🏗️ Does #Science have a structural problem? 🧬

The classic science building is showing deep cracks! For centuries, the #paradigm of #dualism has permeated #ontology and #epistemology.

🎧 Listen to the new podcast episode right now in your Studio Panel!

https://open.spotify.com/episode/2aWB30JYbEhGkTzK7IQmaN?si=6_P7U43eT-aQ_C2tOxNnYw

#PhilosophyOfScience #ParadigmShift #StructuralRealism #Philosophy #Podcast #philosophies_de

The #Paradigm Shift – Renovating the Dualistic Structure of Science

🏗️ Does #Science have a structural problem? 🧬

The classic science building is showing deep cracks! For centuries, the #paradigm of #dualism has permeated #ontology and #epistemology.

🎧 Listen to the new podcast episode right now in your Studio Panel!

https://open.spotify.com/episode/2aWB30JYbEhGkTzK7IQmaN?si=6_P7U43eT-aQ_C2tOxNnYw

#PhilosophyOfScience #ParadigmShift #StructuralRealism #Philosophy #Podcast #philosophies_de

The #Paradigm Shift – Renovating the Dualistic Structure of Science

🏗️ Does #Science have a structural problem? 🧬

The classic science building is showing deep cracks! For centuries, the #paradigm of #dualism has permeated #ontology and #epistemology.

🎧 Listen to the new podcast episode right now in your Studio Panel!

https://open.spotify.com/episode/2aWB30JYbEhGkTzK7IQmaN?si=6_P7U43eT-aQ_C2tOxNnYw

#PhilosophyOfScience #ParadigmShift #StructuralRealism #Philosophy #Podcast #philosophies_de

The #Paradigm Shift – Renovating the Dualistic Structure of Science

🏗️ Does #Science have a structural problem? 🧬

The classic science building is showing deep cracks! For centuries, the #paradigm of #dualism has permeated #ontology and #epistemology.

🎧 Listen to the new podcast episode right now in your Studio Panel!

https://open.spotify.com/episode/2aWB30JYbEhGkTzK7IQmaN?si=6_P7U43eT-aQ_C2tOxNnYw

#PhilosophyOfScience #ParadigmShift #StructuralRealism #Philosophy #Podcast #philosophies_de

The #Paradigm Shift – Renovating the Dualistic Structure of Science

🏗️ Does #Science have a structural problem? 🧬

The classic science building is showing deep cracks! For centuries, the #paradigm of #dualism has permeated #ontology and #epistemology.

🎧 Listen to the new podcast episode right now in your Studio Panel!

https://open.spotify.com/episode/2aWB30JYbEhGkTzK7IQmaN?si=6_P7U43eT-aQ_C2tOxNnYw

#PhilosophyOfScience #ParadigmShift #StructuralRealism #Philosophy #Podcast #philosophies_de

The Reality of Dreams

https://johnbronze.wordpress.com/2026/07/24/the-reality-of-dreams/

Hegel, le perspectivisme et la vie réflexive du monde

Hegel ne dit pas que l’esprit fabrique le monde : il dit que le monde n’apparaît pas pareil à tous les vivants. Ce qui compte, c’est la forme de vie qui rend certaines choses saillantes, pensables, discutables. L’humain, auto-conscient, vit dans une tension réflexive permanente. #Hegel #Philosophy #Perspectivism #CriticalTheory #Ontology Chez Hegel, l’idéalisme ne consiste ni à dire que la réalité est mentale, ni à…

https://homohortus31.wordpress.com/2026/06/30/hegel-le-perspectivisme-et-la-vie-reflexive-du-monde/

I’ve been reading Žižek and Heidegger lately. Žižek labels himself a Communist (politics), Lacanian (method), and Heideggerian (ontology), so I asked Claude and ChatGPT how I fared.

https://open.substack.com/pub/brywillis634737/p/who-am-i?r=pvxh5&utm_campaign=post-expanded-share&utm_medium=masto

#politics #philosphy #ontology #method #zizek #blog #video #podcast #substack #introspection #extrospection #Wittgenstein #pluralism #perspective #biography #rovelli #being #relata #relationships #philosopher

Is Palantir the most evil company in the world?

Answers on a postcard!

“Palantir is turning the NHS into a tool for mass surveillance”

by Jade-Ruyu Yan and Aman Seth in OpenDemocracy

@uk_politics
@palantirwatch
@NoPalantirInSouthYorkshire
@NHSrCommunity
@nhsactivistrn
@UKLabour
@ZackPolanski

“NHS England’s Federated Data Platform, run primarily by controversial US military contractor Palantir, would give a future UK government the ability to use patients’ healthcare data to unleash unprecedented mass surveillance, experts and technologists have warned”

https://www.opendemocracy.net/palantir-is-turning-the-nhs-into-a-tool-for-mass-surveillance/

#Press #SocialMedia #UK #NHS #FederatedData #Palantir #Surveillance #Israel #PalestinianGenocide #Epstein #Starmer #Labour #GoodLawProject #Resistance #Thiel #Karp #Fascism #Racism #Dictatorship #CIA #Ontology

On Philosophics Blog, I consider how ontological grammar commitments confound English translations of Hegel.

https://philosophics.blog/2026/06/04/titrating-hegel/?utm_source=masto&utm_medium=social

#philosophy #language #hegel #geist #ontologicalgrammar #metaphysics #spirit #mind #languageinsufficiency #translation #blog #podcast #video #ontology

I've argued that property rights are immoral. Now, I've shared a pair of posts that argue at a deeper level. This is the first:

https://brywillis634737.substack.com/p/the-fence-before-the-field

#Philosophy #substack #blog #podcast #language #ontology #criticaltheory #anarchism #politicalphilosophy #politicaleconomy #economics #locke #rousseau #propertyrights #property #privateproperty

A Quick Look at 'The Mind’s Eye'

Intro
"Behind your eyes, there is a feeling of a solid, continuous 'you'—the pilot steering the ship. But what if that feeling is actually a beautiful, complex illusion? In this quick 8-minute exploration of the classic text The Mind’s Eye by Douglas Hofstadter and Daniel Dennett

(see ALT txt)

https://youtu.be/dK4BaYy_yps

#self
#consciousness
#ThoughtExperiments
#philosophy
#ontology
#neurology
#brain
#reductionism
#Hofstadter
#Dennett

What do attention, affordance, salience, and valence have to do with meaning, and what is the architecture of encounter?
https://www.youtube.com/watch?v=NHOmNX3MVrk

#philosophy #philosophics #attention #psychology #salience #valence #affordance #language #ontology #video #meaning #writing #books #nature #environment #mediation

In support of my new book, I'm building a glossary.

https://youtu.be/n-sA5JDoED0

This segment is brought to you by the number 42 and…

#Affordance #Salience #Valence #book #video #philosophy #psychology #encounter #mediation #language #ontology #promotion #Elmo #meow #monograph

David Ingram ja Jonathan Tallant uusivat äsken SEP-entryään presentismistä, https://plato.stanford.edu/entries/presentism/. Sitä lukiessa huomaan välillä hymyileväni. Selitys löytynee kirjoituksen erityisen analyyttisesta ja lukijaa palvelevasta tyylistä, joka näyttää harvinaistuvan tuossakin ensyklopediassa.

Toinen kiintoisa päivitys, Christopher Molen Attention https://plato.stanford.edu/entries/attention/, edustaa pikemmin filosofian naturalisoinnin mukanaan tuomaa, sinänsä ansiokasta empiiris-tieteellisen ajantasan tavoittelua. Se ei samalla tavoin kutittele aikanaan logiikan kautta matematiikka-vammaansa kätellyttä eläkeläistä. Hyytyi myös kenties kuranteimman teeman, huomiotalouden kynnykselle, https://en.wikipedia.org/wiki/Attention_economy

Laadukkaiden filosofis-tieteellisten tekstien verkkainen lukeminen on minulle vähän kuin vuolemista (whittling, carving), ja korvannee kohdallani ulkomaanmatkat, viihteen ja fantasiakirjallisuuden.

#sep #philosophy #filosofia #presentism #aika #time #ontology #metafysiikka #analytic #attention #huomio #actualism #possibilism #logic #psykologia #psychology #space #truth #cognition #science #consciousness #travel #lukeminen #kirjallisuus #vuoleminen

So, I had an experience with an influencer account on the fediverse: @FediTips

People believe they are being informed when they are being influenced. That account is litterally publishing what are technically definitionally manifestos.

That emphasized why I don’t argue online. There is an interesting property about facts: factual ontological propositions about something will converge. That is a fancy way of saying that if something is factual, it would be corroborated. Accuracy is not the only important thing; precision is, too. The more corroborative aspects that converge on that claim, the more precise it is. That is why in science, replication and a lot of measurements are so important.

When we talk about online conversations, this is important because if I say something is a fact, and there is a source I got it from, I should cite where I got it. If I or other sources are citing that or a different source saying something, it at least makes the statement more precise, albeit not necessarily more accurate. Accuracy means is a close, approximate representation whereas precision is something is consistent. If you hit the bulls eye once but never again, that is accurate but imprecise. If you never hit the bulls eye but always hit the same spot, that is precise. You can be inaccurate yet precise.

That means if something makes a claim, a source exists, and you can check that claim by visiting the source. If there are multiple sources making the same claim, it is a precise claim.The issue I have with arguments online, for example, endless arguments on Mastodon about Bluesky, is that the sources backing whatever facts I would present are accessible. So, if someone makes a statement about the AT protocol and you say that is wrong, you can look at the documentation, point this out, and say it is wrong because x, y, and z.

That brings me to the fuckery of today:

@FediTips said to me today:

No, you cannot run your own server on AT. Bluesky have made it virtually impossible to set up independent infrastructure. You can store data, but the connections to others run through Bluesky corporation’s infrastructure which they control.

I shit on Bluesky all day, every day, so I’m not a Bluesky stan. But all you have to do is think about why this doesn’t make sense. They are essentially saying that you cannot have a server running a Bluesky PDS that isn’t owned by Bluesky. One, that is not how servers work. A protocol is a way for devices to talk to one another and network.

A network protocol is a formal specification that defines how systems interoperate. It establishes message schemas, authentication mechanisms, transport methods, state transitions, and other rules governing communication between nodes. If multiple servers implement the same protocol specification correctly, they can exchange data and participate in the same network. At the protocol layer, interoperability is determined by adherence to the specification, not by who owns or operates a given server.

Protocol compliance does not inherently guarantee open or permissionless participation. In the architecture of protocols, operators impose constraints through licensing terms, cryptographic trust roots, certificate authorities, service discovery mechanisms, federation allowlists, or other gatekeeping controls. Protocols enable independent servers to communicate; however, it does not logically follow that any compliant server must be accepted into the broader network without additional policy or governance constraints. This is the point they are making.

However, they are conflating who owns the server with what can be allowed in the network. But what they argue for the AT protocol always applies to the ActivityPub protocol. They specifically said, “No, you cannot run your own server on AT. Bluesky has made it virtually impossible to set up independent infrastructure.”

No, you can absolutely run your own independent server that communicates over the AT protocol. Either they understand this and are arguing in bad faith, which I think is very likely, or they are completely disinterested in facts. They merely want to spread and enforce a cultural and political norm. Maybe it’s both.

For example, I am using the ActivityPub protocol to post this, and it is sent to your folks’ inboxes via ActivityStreams through the WordPress ActivityPub plugin. Anyone can set up their own servers on their own hosts. I know for a fact that some feeds are being run off Raspberry Pis in people’s closets. In fact, some people have both fediverse instances and AT protocol PDSs running off the same Raspberry Pis in their closets. By this person’s reasoning, that would imply that Bluesky owns their ISPs, the closets, and the Raspberry Pis.

Yes, the practical network experience heavily depends on Bluesky-operated infrastructure. And yes, it is true that this is different from something like Mastodon on ActivityPub, where federation between independently operated servers is widely distributed and actually decentralized. I’m not contesting that the infrastructure is heavily dependent on and operated by Bluesky.

That’s not the claim @FediTips made. The claim they made is that everyone else’s computers—a cloud is just someone else’s computer, mind you—that use the AT protocol are owned by Bluesky. This statement is so absurd to me that I am not sure if this was a semantic error and not what they meant, or if it is exactly what they meant. If it is the former, it is still bad, because they were disinterested in fact-checking, which is my point. If they bothered to fact-check, they would have caught the inaccuracy or the semantic error.

Secondly, let’s say you know nothing at all about servers, protocols, etc.—you can just look it up.

https://atproto.com/guides/self-hosting

https://docs.digitalocean.com/products/marketplace/catalog/bluesky-social-pds

I was not aware that DigitalOcean was owned by Bluesky. That’s because they are not owned by Bluesky. DigitalOcean is to an AT protocol PDS what a Mastodon host is to Mastodon. If this person had simply done a five-minute search, they would realize that Bluesky does not own the independent servers for the Bluesky apps, albeit it controls the protocol architecture. Personally, I think @FediTips did it in bad faith, because multiple developers have corrected these Mastodon influencer accounts over and over again. At this point, it is propaganda.

I don’t care about this argument in particular. Rather, it’s an example of why I don’t argue with people online. They don’t check what they say or look up what the other person said because they are disinterested in facts. They are interested in the normative claim and cultural norms they are trying to spread and enforce. It’s basically a form of evangelizing and proselytizing.

Again, I don’t really care for this particular argument, which is why I never directly addressed it with them. What I am saying is that they were disinterested in easily accessible facts, so arguing with them to persuade them is a waste of my time.

People on social media care about culture first and facts second. I am not going after the people on Mastodon specifically. Redditors are infamous for this shit. If you ask me, Reddit and Discord are ground zero cases for this dumbass culture of reply guys.

I wrote my own Bayesian classifier and Markov algorithm a long time ago that curate only what I want to see in activity streams, so I don’t see whatever fuckery many of these idiots on social media are doing. I have my own Bayesian and Markov curation algorithm for activity streams and my own algorithm for feeds on Bluesky.

You can see the documentation for how Activity Streams, which is what ActivityPub uses, works here:

Activity Streams 2.0

https://www.w3.org/TR/activitystreams-core

I curate the ActivityStream of my inbox points to see posts based on relevance rather than chronological order. Most of the time, their nonsense is filtered out. I just had time to kill.

So, I had an experience with an influencer account on the fediverse: @FediTips

People believe they are being informed when they are being influenced. That account is litterally publishing what are technically definitionally manifestos.

That emphasized why I don’t argue online. There is an interesting property about facts: factual ontological propositions about something will converge. That is a fancy way of saying that if something is factual, it would be corroborated. Accuracy is not the only important thing; precision is, too. The more corroborative aspects that converge on that claim, the more precise it is. That is why in science, replication and a lot of measurements are so important.

When we talk about online conversations, this is important because if I say something is a fact, and there is a source I got it from, I should cite where I got it. If I or other sources are citing that or a different source saying something, it at least makes the statement more precise, albeit not necessarily more accurate. Accuracy means is a close, approximate representation whereas precision is something is consistent. If you hit the bulls eye once but never again, that is accurate but imprecise. If you never hit the bulls eye but always hit the same spot, that is precise. You can be inaccurate yet precise.

That means if something makes a claim, a source exists, and you can check that claim by visiting the source. If there are multiple sources making the same claim, it is a precise claim.The issue I have with arguments online, for example, endless arguments on Mastodon about Bluesky, is that the sources backing whatever facts I would present are accessible. So, if someone makes a statement about the AT protocol and you say that is wrong, you can look at the documentation, point this out, and say it is wrong because x, y, and z.

That brings me to the fuckery of today:

@FediTips said to me today:

No, you cannot run your own server on AT. Bluesky have made it virtually impossible to set up independent infrastructure. You can store data, but the connections to others run through Bluesky corporation’s infrastructure which they control.

I shit on Bluesky all day, every day, so I’m not a Bluesky stan. But all you have to do is think about why this doesn’t make sense. They are essentially saying that you cannot have a server running a Bluesky PDS that isn’t owned by Bluesky. One, that is not how servers work. A protocol is a way for devices to talk to one another and network.

A network protocol is a formal specification that defines how systems interoperate. It establishes message schemas, authentication mechanisms, transport methods, state transitions, and other rules governing communication between nodes. If multiple servers implement the same protocol specification correctly, they can exchange data and participate in the same network. At the protocol layer, interoperability is determined by adherence to the specification, not by who owns or operates a given server.

Protocol compliance does not inherently guarantee open or permissionless participation. In the architecture of protocols, operators impose constraints through licensing terms, cryptographic trust roots, certificate authorities, service discovery mechanisms, federation allowlists, or other gatekeeping controls. Protocols enable independent servers to communicate; however, it does not logically follow that any compliant server must be accepted into the broader network without additional policy or governance constraints. This is the point they are making.

However, they are conflating who owns the server with what can be allowed in the network. But what they argue for the AT protocol always applies to the ActivityPub protocol. They specifically said, “No, you cannot run your own server on AT. Bluesky has made it virtually impossible to set up independent infrastructure.”

No, you can absolutely run your own independent server that communicates over the AT protocol. Either they understand this and are arguing in bad faith, which I think is very likely, or they are completely disinterested in facts. They merely want to spread and enforce a cultural and political norm. Maybe it’s both.

For example, I am using the ActivityPub protocol to post this, and it is sent to your folks’ inboxes via ActivityStreams through the WordPress ActivityPub plugin. Anyone can set up their own servers on their own hosts. I know for a fact that some feeds are being run off Raspberry Pis in people’s closets. In fact, some people have both fediverse instances and AT protocol PDSs running off the same Raspberry Pis in their closets. By this person’s reasoning, that would imply that Bluesky owns their ISPs, the closets, and the Raspberry Pis.

Yes, the practical network experience heavily depends on Bluesky-operated infrastructure. And yes, it is true that this is different from something like Mastodon on ActivityPub, where federation between independently operated servers is widely distributed and actually decentralized. I’m not contesting that the infrastructure is heavily dependent on and operated by Bluesky.

That’s not the claim @FediTips made. The claim they made is that everyone else’s computers—a cloud is just someone else’s computer, mind you—that use the AT protocol are owned by Bluesky. This statement is so absurd to me that I am not sure if this was a semantic error and not what they meant, or if it is exactly what they meant. If it is the former, it is still bad, because they were disinterested in fact-checking, which is my point. If they bothered to fact-check, they would have caught the inaccuracy or the semantic error.

Secondly, let’s say you know nothing at all about servers, protocols, etc.—you can just look it up.

https://atproto.com/guides/self-hosting

https://docs.digitalocean.com/products/marketplace/catalog/bluesky-social-pds

I was not aware that DigitalOcean was owned by Bluesky. That’s because they are not owned by Bluesky. DigitalOcean is to an AT protocol PDS what a Mastodon host is to Mastodon. If this person had simply done a five-minute search, they would realize that Bluesky does not own the independent servers for the Bluesky apps, albeit it controls the protocol architecture. Personally, I think @FediTips did it in bad faith, because multiple developers have corrected these Mastodon influencer accounts over and over again. At this point, it is propaganda.

I don’t care about this argument in particular. Rather, it’s an example of why I don’t argue with people online. They don’t check what they say or look up what the other person said because they are disinterested in facts. They are interested in the normative claim and cultural norms they are trying to spread and enforce. It’s basically a form of evangelizing and proselytizing.

Again, I don’t really care for this particular argument, which is why I never directly addressed it with them. What I am saying is that they were disinterested in easily accessible facts, so arguing with them to persuade them is a waste of my time.

People on social media care about culture first and facts second. I am not going after the people on Mastodon specifically. Redditors are infamous for this shit. If you ask me, Reddit and Discord are ground zero cases for this dumbass culture of reply guys.

I wrote my own Bayesian classifier and Markov algorithm a long time ago that curate only what I want to see in activity streams, so I don’t see whatever fuckery many of these idiots on social media are doing. I have my own Bayesian and Markov curation algorithm for activity streams and my own algorithm for feeds on Bluesky.

You can see the documentation for how Activity Streams, which is what ActivityPub uses, works here:

Activity Streams 2.0

https://www.w3.org/TR/activitystreams-core

I curate the ActivityStream of my inbox points to see posts based on relevance rather than chronological order. Most of the time, their nonsense is filtered out. I just had time to kill.

So, I had an experience with an influencer account on the fediverse: @FediTips

People believe they are being informed when they are being influenced. That account is litterally publishing what are technically definitionally manifestos.

That emphasized why I don’t argue online. There is an interesting property about facts: factual ontological propositions about something will converge. That is a fancy way of saying that if something is factual, it would be corroborated. Accuracy is not the only important thing; precision is, too. The more corroborative aspects that converge on that claim, the more precise it is. That is why in science, replication and a lot of measurements are so important.

When we talk about online conversations, this is important because if I say something is a fact, and there is a source I got it from, I should cite where I got it. If I or other sources are citing that or a different source saying something, it at least makes the statement more precise, albeit not necessarily more accurate. Accuracy means is a close, approximate representation whereas precision is something is consistent. If you hit the bulls eye once but never again, that is accurate but imprecise. If you never hit the bulls eye but always hit the same spot, that is precise. You can be inaccurate yet precise.

That means if something makes a claim, a source exists, and you can check that claim by visiting the source. If there are multiple sources making the same claim, it is a precise claim.The issue I have with arguments online, for example, endless arguments on Mastodon about Bluesky, is that the sources backing whatever facts I would present are accessible. So, if someone makes a statement about the AT protocol and you say that is wrong, you can look at the documentation, point this out, and say it is wrong because x, y, and z.

That brings me to the fuckery of today:

@FediTips said to me today:

No, you cannot run your own server on AT. Bluesky have made it virtually impossible to set up independent infrastructure. You can store data, but the connections to others run through Bluesky corporation’s infrastructure which they control.

I shit on Bluesky all day, every day, so I’m not a Bluesky stan. But all you have to do is think about why this doesn’t make sense. They are essentially saying that you cannot have a server running a Bluesky PDS that isn’t owned by Bluesky. One, that is not how servers work. A protocol is a way for devices to talk to one another and network.

A network protocol is a formal specification that defines how systems interoperate. It establishes message schemas, authentication mechanisms, transport methods, state transitions, and other rules governing communication between nodes. If multiple servers implement the same protocol specification correctly, they can exchange data and participate in the same network. At the protocol layer, interoperability is determined by adherence to the specification, not by who owns or operates a given server.

Protocol compliance does not inherently guarantee open or permissionless participation. In the architecture of protocols, operators impose constraints through licensing terms, cryptographic trust roots, certificate authorities, service discovery mechanisms, federation allowlists, or other gatekeeping controls. Protocols enable independent servers to communicate; however, it does not logically follow that any compliant server must be accepted into the broader network without additional policy or governance constraints. This is the point they are making.

However, they are conflating who owns the server with what can be allowed in the network. But what they argue for the AT protocol always applies to the ActivityPub protocol. They specifically said, “No, you cannot run your own server on AT. Bluesky has made it virtually impossible to set up independent infrastructure.”

No, you can absolutely run your own independent server that communicates over the AT protocol. Either they understand this and are arguing in bad faith, which I think is very likely, or they are completely disinterested in facts. They merely want to spread and enforce a cultural and political norm. Maybe it’s both.

For example, I am using the ActivityPub protocol to post this, and it is sent to your folks’ inboxes via ActivityStreams through the WordPress ActivityPub plugin. Anyone can set up their own servers on their own hosts. I know for a fact that some feeds are being run off Raspberry Pis in people’s closets. In fact, some people have both fediverse instances and AT protocol PDSs running off the same Raspberry Pis in their closets. By this person’s reasoning, that would imply that Bluesky owns their ISPs, the closets, and the Raspberry Pis.

Yes, the practical network experience heavily depends on Bluesky-operated infrastructure. And yes, it is true that this is different from something like Mastodon on ActivityPub, where federation between independently operated servers is widely distributed and actually decentralized. I’m not contesting that the infrastructure is heavily dependent on and operated by Bluesky.

That’s not the claim @FediTips made. The claim they made is that everyone else’s computers—a cloud is just someone else’s computer, mind you—that use the AT protocol are owned by Bluesky. This statement is so absurd to me that I am not sure if this was a semantic error and not what they meant, or if it is exactly what they meant. If it is the former, it is still bad, because they were disinterested in fact-checking, which is my point. If they bothered to fact-check, they would have caught the inaccuracy or the semantic error.

Secondly, let’s say you know nothing at all about servers, protocols, etc.—you can just look it up.

https://atproto.com/guides/self-hosting

https://docs.digitalocean.com/products/marketplace/catalog/bluesky-social-pds

I was not aware that DigitalOcean was owned by Bluesky. That’s because they are not owned by Bluesky. DigitalOcean is to an AT protocol PDS what a Mastodon host is to Mastodon. If this person had simply done a five-minute search, they would realize that Bluesky does not own the independent servers for the Bluesky apps, albeit it controls the protocol architecture. Personally, I think @FediTips did it in bad faith, because multiple developers have corrected these Mastodon influencer accounts over and over again. At this point, it is propaganda.

I don’t care about this argument in particular. Rather, it’s an example of why I don’t argue with people online. They don’t check what they say or look up what the other person said because they are disinterested in facts. They are interested in the normative claim and cultural norms they are trying to spread and enforce. It’s basically a form of evangelizing and proselytizing.

Again, I don’t really care for this particular argument, which is why I never directly addressed it with them. What I am saying is that they were disinterested in easily accessible facts, so arguing with them to persuade them is a waste of my time.

People on social media care about culture first and facts second. I am not going after the people on Mastodon specifically. Redditors are infamous for this shit. If you ask me, Reddit and Discord are ground zero cases for this dumbass culture of reply guys.

I wrote my own Bayesian classifier and Markov algorithm a long time ago that curate only what I want to see in activity streams, so I don’t see whatever fuckery many of these idiots on social media are doing. I have my own Bayesian and Markov curation algorithm for activity streams and my own algorithm for feeds on Bluesky.

You can see the documentation for how Activity Streams, which is what ActivityPub uses, works here:

Activity Streams 2.0

https://www.w3.org/TR/activitystreams-core

I curate the ActivityStream of my inbox points to see posts based on relevance rather than chronological order. Most of the time, their nonsense is filtered out. I just had time to kill.

A colleague and I chatted about a recent publication; he graciously noted he didn't agree with me. I realise that my example was strictly US. In this post, I don't lose the US frame; I added more background and brought in some name support. Feedback and counterpoints welcome.
👉 https://philosophics.blog/2026/02/12/the-architecture-of-cognitive-compromise/?utm_source=masto&utm_medium=social
#philosophy #morals #ethics #thickness #legibility #ontology #biopower #habitus #paradox #tolerance #epistemology #abortion #rights #culture #frameworks #society #blog #podcast #communication

Your BlueSky Feed Is Porn You Didn’t Ask For Because Your Friends Are Gooners With a Severe Porn Addiction

A common complaint I see people make on Bluesky is: why am I being served so much porn or things I am not interested in? They will incorrectly believe that the algorithm is broken. It’s not broken. You didn’t know the people you knew as well as you thought you did. Porn addiction is a thing, and porn addiction is especially common with weebs. You’re seeing deranged shit because people you follow have porn addictions and are into deranged shit. So, though you may not be consuming porn, people in your network are. That activity kicks into your feeds.

The issue I have with that is that it essentially normalizes being sex pests in a space on the Internet. That sets the expectation that it is good—attractive, even—to act like that elsewhere. That expectation alienates relationships. Bluesky creates a cultural space that offers an unrealistic, bizarre representation of social relationships, which isolates and alienates the users who stay on there consuming erotica and porn like they do.

So, user repos in Bluesky have a property for likes. Bluesky’s underlying AT Protocol stores likes as first-class structured records in each user’s AT Protocol repository. In the AT Protocol lexicon, a like is an app.bsky.feed.like record type. Unlike a simple boolean flag on a post, it is its own record with a creation timestamp and a subject field that holds a strong reference to the liked record.

That strong reference is composed of an AT-URI and a CID. The AT-URI identifies the exact record in the network by DID, collection, and record key. The CID is a cryptographic content identifier that uniquely identifies the exact content of that liked record.

These like records exist under the app.bsky.feed.like namespace in the user’s repo. Bluesky’s repo model is built so that these repos are hosted on a user’s Personal Data Server and are publicly readable through the AT Protocol APIs. Because of that, the like record and its fields can be fetched, indexed, and used by any client or service that can query the protocol.

The protocol exposes operations like getLikes. This returns all of the like records tied to a particular subject’s AT-URI and CID. It also exposes getActorLikes. This returns all of the subject references a given actor has liked. Those API calls return structured like objects with timestamps and subject references directly from the public repository data.

Various feeds hosted by different PDSs use the likes property to construct the feeds that you see. Since the likes of people you follow are included in your social graph, along with your own likes, you’re going to get served the porn they are consuming. Because likes are public and anyone can write an algorithm to see everyone’s likes, you can clearly see just how much porn people are consuming.

Honestly, what started to turn my stomach about the people on Bluesky is how they behave across different contexts. If you look through the records of the posts they interact with, you’ll see them engaging with political posts in the replies like a normal person. Then, when you look through their AT Protocol records, you see hours and hours of them interacting with every kind of porn imaginable. I am not exaggerating. Hours of likes for porn posts within 1–10 minutes of each other. Am I sex-negative? A prude? No, this site is filled with furry, gay bara porn, lol. You can have a drink without being an alcoholic. The problem with these people is like people who can’t have one drink without drinking the whole fucking day; they can’t consume porn in healthy ways.

I think people assume that their feed is customized for them and based on their likes. No—feeds are generalized based on what everyone likes and then served to your subgraph. It’s not just about who you follow; it’s about who they follow. So if you follow someone who follows a lot of people with porn addictions, you will see porn. Bluesky isn’t weighting the algorithm to do this. Basically, it’s the people in your social network with furry, hentai, or trans porn addictions who are driving it.

Your BlueSky Feed Is Porn You Didn’t Ask For Because Your Friends Are Gooners With a Severe Porn Addiction

A common complaint I see people make on Bluesky is: why am I being served so much porn or things I am not interested in? They will incorrectly believe that the algorithm is broken. It’s not broken. You didn’t know the people you knew as well as you thought you did. Porn addiction is a thing, and porn addiction is especially common with weebs. You’re seeing deranged shit because people you follow have porn addictions and are into deranged shit. So, though you may not be consuming porn, people in your network are. That activity kicks into your feeds.

The issue I have with that is that it essentially normalizes being sex pests in a space on the Internet. That sets the expectation that it is good—attractive, even—to act like that elsewhere. That expectation alienates relationships. Bluesky creates a cultural space that offers an unrealistic, bizarre representation of social relationships, which isolates and alienates the users who stay on there consuming erotica and porn like they do.

So, user repos in Bluesky have a property for likes. Bluesky’s underlying AT Protocol stores likes as first-class structured records in each user’s AT Protocol repository. In the AT Protocol lexicon, a like is an app.bsky.feed.like record type. Unlike a simple boolean flag on a post, it is its own record with a creation timestamp and a subject field that holds a strong reference to the liked record.

That strong reference is composed of an AT-URI and a CID. The AT-URI identifies the exact record in the network by DID, collection, and record key. The CID is a cryptographic content identifier that uniquely identifies the exact content of that liked record.

These like records exist under the app.bsky.feed.like namespace in the user’s repo. Bluesky’s repo model is built so that these repos are hosted on a user’s Personal Data Server and are publicly readable through the AT Protocol APIs. Because of that, the like record and its fields can be fetched, indexed, and used by any client or service that can query the protocol.

The protocol exposes operations like getLikes. This returns all of the like records tied to a particular subject’s AT-URI and CID. It also exposes getActorLikes. This returns all of the subject references a given actor has liked. Those API calls return structured like objects with timestamps and subject references directly from the public repository data.

Various feeds hosted by different PDSs use the likes property to construct the feeds that you see. Since the likes of people you follow are included in your social graph, along with your own likes, you’re going to get served the porn they are consuming. Because likes are public and anyone can write an algorithm to see everyone’s likes, you can clearly see just how much porn people are consuming.

Honestly, what started to turn my stomach about the people on Bluesky is how they behave across different contexts. If you look through the records of the posts they interact with, you’ll see them engaging with political posts in the replies like a normal person. Then, when you look through their AT Protocol records, you see hours and hours of them interacting with every kind of porn imaginable. I am not exaggerating. Hours of likes for porn posts within 1–10 minutes of each other. Am I sex-negative? A prude? No, this site is filled with furry, gay bara porn, lol. You can have a drink without being an alcoholic. The problem with these people is like people who can’t have one drink without drinking the whole fucking day; they can’t consume porn in healthy ways.

I think people assume that their feed is customized for them and based on their likes. No—feeds are generalized based on what everyone likes and then served to your subgraph. It’s not just about who you follow; it’s about who they follow. So if you follow someone who follows a lot of people with porn addictions, you will see porn. Bluesky isn’t weighting the algorithm to do this. Basically, it’s the people in your social network with furry, hentai, or trans porn addictions who are driving it.

Your BlueSky Feed Is Porn You Didn’t Ask For Because Your Friends Are Gooners With a Severe Porn Addiction

A common complaint I see people make on Bluesky is: why am I being served so much porn or things I am not interested in? They will incorrectly believe that the algorithm is broken. It’s not broken. You didn’t know the people you knew as well as you thought you did. Porn addiction is a thing, and porn addiction is especially common with weebs. You’re seeing deranged shit because people you follow have porn addictions and are into deranged shit. So, though you may not be consuming porn, people in your network are. That activity kicks into your feeds.

The issue I have with that is that it essentially normalizes being sex pests in a space on the Internet. That sets the expectation that it is good—attractive, even—to act like that elsewhere. That expectation alienates relationships. Bluesky creates a cultural space that offers an unrealistic, bizarre representation of social relationships, which isolates and alienates the users who stay on there consuming erotica and porn like they do.

So, user repos in Bluesky have a property for likes. Bluesky’s underlying AT Protocol stores likes as first-class structured records in each user’s AT Protocol repository. In the AT Protocol lexicon, a like is an app.bsky.feed.like record type. Unlike a simple boolean flag on a post, it is its own record with a creation timestamp and a subject field that holds a strong reference to the liked record.

That strong reference is composed of an AT-URI and a CID. The AT-URI identifies the exact record in the network by DID, collection, and record key. The CID is a cryptographic content identifier that uniquely identifies the exact content of that liked record.

These like records exist under the app.bsky.feed.like namespace in the user’s repo. Bluesky’s repo model is built so that these repos are hosted on a user’s Personal Data Server and are publicly readable through the AT Protocol APIs. Because of that, the like record and its fields can be fetched, indexed, and used by any client or service that can query the protocol.

The protocol exposes operations like getLikes. This returns all of the like records tied to a particular subject’s AT-URI and CID. It also exposes getActorLikes. This returns all of the subject references a given actor has liked. Those API calls return structured like objects with timestamps and subject references directly from the public repository data.

Various feeds hosted by different PDSs use the likes property to construct the feeds that you see. Since the likes of people you follow are included in your social graph, along with your own likes, you’re going to get served the porn they are consuming. Because likes are public and anyone can write an algorithm to see everyone’s likes, you can clearly see just how much porn people are consuming.

Honestly, what started to turn my stomach about the people on Bluesky is how they behave across different contexts. If you look through the records of the posts they interact with, you’ll see them engaging with political posts in the replies like a normal person. Then, when you look through their AT Protocol records, you see hours and hours of them interacting with every kind of porn imaginable. I am not exaggerating. Hours of likes for porn posts within 1–10 minutes of each other. Am I sex-negative? A prude? No, this site is filled with furry, gay bara porn, lol. You can have a drink without being an alcoholic. The problem with these people is like people who can’t have one drink without drinking the whole fucking day; they can’t consume porn in healthy ways.

I think people assume that their feed is customized for them and based on their likes. No—feeds are generalized based on what everyone likes and then served to your subgraph. It’s not just about who you follow; it’s about who they follow. So if you follow someone who follows a lot of people with porn addictions, you will see porn. Bluesky isn’t weighting the algorithm to do this. Basically, it’s the people in your social network with furry, hentai, or trans porn addictions who are driving it.

Your BlueSky Feed Is Porn You Didn’t Ask For Because Your Friends Are Gooners With a Severe Porn Addiction

A common complaint I see people make on Bluesky is: why am I being served so much porn or things I am not interested in? They will incorrectly believe that the algorithm is broken. It’s not broken. You didn’t know the people you knew as well as you thought you did. Porn addiction is a thing, and porn addiction is especially common with weebs. You’re seeing deranged shit because people you follow have porn addictions and are into deranged shit. So, though you may not be consuming porn, people in your network are. That activity kicks into your feeds.

The issue I have with that is that it essentially normalizes being sex pests in a space on the Internet. That sets the expectation that it is good—attractive, even—to act like that elsewhere. That expectation alienates relationships. Bluesky creates a cultural space that offers an unrealistic, bizarre representation of social relationships, which isolates and alienates the users who stay on there consuming erotica and porn like they do.

So, user repos in Bluesky have a property for likes. Bluesky’s underlying AT Protocol stores likes as first-class structured records in each user’s AT Protocol repository. In the AT Protocol lexicon, a like is an app.bsky.feed.like record type. Unlike a simple boolean flag on a post, it is its own record with a creation timestamp and a subject field that holds a strong reference to the liked record.

That strong reference is composed of an AT-URI and a CID. The AT-URI identifies the exact record in the network by DID, collection, and record key. The CID is a cryptographic content identifier that uniquely identifies the exact content of that liked record.

These like records exist under the app.bsky.feed.like namespace in the user’s repo. Bluesky’s repo model is built so that these repos are hosted on a user’s Personal Data Server and are publicly readable through the AT Protocol APIs. Because of that, the like record and its fields can be fetched, indexed, and used by any client or service that can query the protocol.

The protocol exposes operations like getLikes. This returns all of the like records tied to a particular subject’s AT-URI and CID. It also exposes getActorLikes. This returns all of the subject references a given actor has liked. Those API calls return structured like objects with timestamps and subject references directly from the public repository data.

Various feeds hosted by different PDSs use the likes property to construct the feeds that you see. Since the likes of people you follow are included in your social graph, along with your own likes, you’re going to get served the porn they are consuming. Because likes are public and anyone can write an algorithm to see everyone’s likes, you can clearly see just how much porn people are consuming.

Honestly, what started to turn my stomach about the people on Bluesky is how they behave across different contexts. If you look through the records of the posts they interact with, you’ll see them engaging with political posts in the replies like a normal person. Then, when you look through their AT Protocol records, you see hours and hours of them interacting with every kind of porn imaginable. I am not exaggerating. Hours of likes for porn posts within 1–10 minutes of each other. Am I sex-negative? A prude? No, this site is filled with furry, gay bara porn, lol. You can have a drink without being an alcoholic. The problem with these people is like people who can’t have one drink without drinking the whole fucking day; they can’t consume porn in healthy ways.

I think people assume that their feed is customized for them and based on their likes. No—feeds are generalized based on what everyone likes and then served to your subgraph. It’s not just about who you follow; it’s about who they follow. So if you follow someone who follows a lot of people with porn addictions, you will see porn. Bluesky isn’t weighting the algorithm to do this. Basically, it’s the people in your social network with furry, hentai, or trans porn addictions who are driving it.

BlueSky’s Solution To Moderating Is Moderating Without Moderating via Social Proximity

I have noticed a lot of people are confused about why some posts don’t show up on threads, though they are not labeled by the moderation layer. Bluesky has begun using what it calls social neighborhoods (or network proximity) as a ranking signal for replies in threads. Replies from people who are closer to you in the social graph, accounts you follow, interact with, or share mutual connections with, are prioritized and shown more prominently. Replies from accounts that are farther away in that network are down-ranked. They are pushed far down the thread or placed behind “hidden replies.”

Each person gets their own unique view of a thread based on their social graph. It creates the impression that replies from distant users simply don’t exist. This is true even though they’re still technically public and viewable if you expand the thread or adjust filters. Bluesky is explicitly using features of subgraphs to moderate without moderating. Their reasoning is that if you can’t see each other, you can’t harass each other. Ergo, there is nothing to moderate.

Bluesky mentions that here:

https://bsky.social/about/blog/10-31-2025-building-healthier-social-media-update

As a digression, I’m not going to lie: I really enjoyed working on software built on the AT protocol, but their fucking users are so goddamn weird. It’s sort of like enjoying building houses, but hating every single person who moves into them. But, you don’t have to deal with them because you’re just the contractor. That is how I feel about Bluesky. I hate the people. I really like the protocol and infrastructure.

I sort of am a sadist who does enjoy drama, so I do get schadenfreude from people with social media addictions and parasocial fixations who reply to random people on Bluesky, because they don’t realize their replies are disconnected from the author’s thread unless that person is within their network. They aren’t part of the conversation they think they are. They’re algorithmically isolated from everyone else. Their replies aren’t viewable from the author’s thread because of how Bluesky handles social neighborhoods.

Bluesky’s idea of social neighborhoods is about grouping users into overlapping clusters based on real interaction patterns rather than just the follow graph. Unlike Twitter, it does not treat the network as one big public square. Instead, it models networks of “social neighborhoods” made up of people you follow, people who follow you, people you frequently interact with, and people who are closely connected to those groups. They’re soft, probabilistic groupings rather than strict labels.

Everyone does not see the same replies. Bluesky is being a bit vague with “hidden.” Hidden means your reply is still anchored to the thread and can be expanded. There is another way Bluesky can handle this. Bluesky uses social neighborhoods to judge contextual relevance. Replies from people inside or near your social neighborhood are more likely to be shown inline with a thread, expanded by default, or served in feeds. Replies from outside your neighborhood are still public and still indexed, but they’re treated as lower-context contributions.

Basically, if you reply to a thread, you will see it anchored to the conversation, and everyone will see it in search results, as a hashtag, or from your profile, but it will not be accessible via the thread of the person you were replying to. It is like shadow-banning people from threads unless they are strongly networked.

Because people have not been working with the AT Protocol like I have, they assume they are shadow-banned across the entire Bluesky app view. No—everyone is automatically shadow-banned from everyone else unless they are within the same social neighborhood. In other words, you are not part of the conversation you think you are joining because you are not part of their social group.

Your replies will appear in profiles, hashtag feeds, or search results without being visually anchored to the full thread. Discovery impressions are neighborhood-agnostic: they serve content because it matches a query, tag, or activity stream. Once the reply is shown, the app then decides whether it’s worth pulling in the rest of the conversation for you. If the original author and most participants fall outside your neighborhood, Bluesky often chooses not to expand that context automatically.

Bluesky really is trying to avoid having to moderate, so this is their solution. Instead of banning or issuing takedown labels to DIDs, the system lets replies exist everywhere, but not in that particular instance of the thread.

I find this ironic because a large reason why many people are staying on Bluesky and not moving to the fediverse—thank God, because I do not want them there—is discoverability, virality, and engagement.

In case anyone is asking how I know so much about how these algorithms work: I was a consultant on a lot of these types of algorithms, so I certainly hope I’d know how they work, lol. No, you get no more details about the work I’ve done. I have no hand in the algorithm Bluesky is using, but I have proposed and implemented that type of algorithm before.

I have an interest in noetics and the noosphere. A large amount of my ontological work is an extension of my attempts to model domains that have no spatial or temporal coordinates. The question is how do you generalize a metric space that has no physically, spatial properties. I went to school to try to formalize those ideas. Turns out they’re rather useful for digital social networks, too. The ontological analog to spatial distance, when you have no space, is a graph of similarities.

BlueSky’s Solution To Moderating Is Moderating Without Moderating via Social Proximity

I have noticed a lot of people are confused about why some posts don’t show up on threads, though they are not labeled by the moderation layer. Bluesky has begun using what it calls social neighborhoods (or network proximity) as a ranking signal for replies in threads. Replies from people who are closer to you in the social graph, accounts you follow, interact with, or share mutual connections with, are prioritized and shown more prominently. Replies from accounts that are farther away in that network are down-ranked. They are pushed far down the thread or placed behind “hidden replies.”

Each person gets their own unique view of a thread based on their social graph. It creates the impression that replies from distant users simply don’t exist. This is true even though they’re still technically public and viewable if you expand the thread or adjust filters. Bluesky is explicitly using features of subgraphs to moderate without moderating. Their reasoning is that if you can’t see each other, you can’t harass each other. Ergo, there is nothing to moderate.

Bluesky mentions that here:

https://bsky.social/about/blog/10-31-2025-building-healthier-social-media-update

As a digression, I’m not going to lie: I really enjoyed working on software built on the AT protocol, but their fucking users are so goddamn weird. It’s sort of like enjoying building houses, but hating every single person who moves into them. But, you don’t have to deal with them because you’re just the contractor. That is how I feel about Bluesky. I hate the people. I really like the protocol and infrastructure.

I sort of am a sadist who does enjoy drama, so I do get schadenfreude from people with social media addictions and parasocial fixations who reply to random people on Bluesky, because they don’t realize their replies are disconnected from the author’s thread unless that person is within their network. They aren’t part of the conversation they think they are. They’re algorithmically isolated from everyone else. Their replies aren’t viewable from the author’s thread because of how Bluesky handles social neighborhoods.

Bluesky’s idea of social neighborhoods is about grouping users into overlapping clusters based on real interaction patterns rather than just the follow graph. Unlike Twitter, it does not treat the network as one big public square. Instead, it models networks of “social neighborhoods” made up of people you follow, people who follow you, people you frequently interact with, and people who are closely connected to those groups. They’re soft, probabilistic groupings rather than strict labels.

Everyone does not see the same replies. Bluesky is being a bit vague with “hidden.” Hidden means your reply is still anchored to the thread and can be expanded. There is another way Bluesky can handle this. Bluesky uses social neighborhoods to judge contextual relevance. Replies from people inside or near your social neighborhood are more likely to be shown inline with a thread, expanded by default, or served in feeds. Replies from outside your neighborhood are still public and still indexed, but they’re treated as lower-context contributions.

Basically, if you reply to a thread, you will see it anchored to the conversation, and everyone will see it in search results, as a hashtag, or from your profile, but it will not be accessible via the thread of the person you were replying to. It is like shadow-banning people from threads unless they are strongly networked.

Because people have not been working with the AT Protocol like I have, they assume they are shadow-banned across the entire Bluesky app view. No—everyone is automatically shadow-banned from everyone else unless they are within the same social neighborhood. In other words, you are not part of the conversation you think you are joining because you are not part of their social group.

Your replies will appear in profiles, hashtag feeds, or search results without being visually anchored to the full thread. Discovery impressions are neighborhood-agnostic: they serve content because it matches a query, tag, or activity stream. Once the reply is shown, the app then decides whether it’s worth pulling in the rest of the conversation for you. If the original author and most participants fall outside your neighborhood, Bluesky often chooses not to expand that context automatically.

Bluesky really is trying to avoid having to moderate, so this is their solution. Instead of banning or issuing takedown labels to DIDs, the system lets replies exist everywhere, but not in that particular instance of the thread.

I find this ironic because a large reason why many people are staying on Bluesky and not moving to the fediverse—thank God, because I do not want them there—is discoverability, virality, and engagement.

In case anyone is asking how I know so much about how these algorithms work: I was a consultant on a lot of these types of algorithms, so I certainly hope I’d know how they work, lol. No, you get no more details about the work I’ve done. I have no hand in the algorithm Bluesky is using, but I have proposed and implemented that type of algorithm before.

I have an interest in noetics and the noosphere. A large amount of my ontological work is an extension of my attempts to model domains that have no spatial or temporal coordinates. The question is how do you generalize a metric space that has no physically, spatial properties. I went to school to try to formalize those ideas. Turns out they’re rather useful for digital social networks, too. The ontological analog to spatial distance, when you have no space, is a graph of similarities.

This can be modeled by representing each item as a node in a weighted graph, where edges are weighted by dissimilarity rather than similarity. Highly similar items are connected by low-weight edges, while less similar items are connected by higher-weight edges. Distances in the graph, computed using standard shortest-path algorithms, then correspond to degrees of similarity. Closely related items are separated by short path lengths, while increasingly dissimilar items require longer paths through the graph. It turns out that attempts to generalize metric spaces for noetic domains—to model noetic/psychic spaces—are actually pretty useful for social media algorithms, lol.

BlueSky’s Solution To Moderating Is Moderating Without Moderating via Social Proximity

I have noticed a lot of people are confused about why some posts don’t show up on threads, though they are not labeled by the moderation layer. Bluesky has begun using what it calls social neighborhoods (or network proximity) as a ranking signal for replies in threads. Replies from people who are closer to you in the social graph, accounts you follow, interact with, or share mutual connections with, are prioritized and shown more prominently. Replies from accounts that are farther away in that network are down-ranked. They are pushed far down the thread or placed behind “hidden replies.”

Each person gets their own unique view of a thread based on their social graph. It creates the impression that replies from distant users simply don’t exist. This is true even though they’re still technically public and viewable if you expand the thread or adjust filters. Bluesky is explicitly using features of subgraphs to moderate without moderating. Their reasoning is that if you can’t see each other, you can’t harass each other. Ergo, there is nothing to moderate.

Bluesky mentions that here:

https://bsky.social/about/blog/10-31-2025-building-healthier-social-media-update

As a digression, I’m not going to lie: I really enjoyed working on software built on the AT protocol, but their fucking users are so goddamn weird. It’s sort of like enjoying building houses, but hating every single person who moves into them. But, you don’t have to deal with them because you’re just the contractor. That is how I feel about Bluesky. I hate the people. I really like the protocol and infrastructure.

I sort of am a sadist who does enjoy drama, so I do get schadenfreude from people with social media addictions and parasocial fixations who reply to random people on Bluesky, because they don’t realize their replies are disconnected from the author’s thread unless that person is within their network. They aren’t part of the conversation they think they are. They’re algorithmically isolated from everyone else. Their replies aren’t viewable from the author’s thread because of how Bluesky handles social neighborhoods.

Bluesky’s idea of social neighborhoods is about grouping users into overlapping clusters based on real interaction patterns rather than just the follow graph. Unlike Twitter, it does not treat the network as one big public square. Instead, it models networks of “social neighborhoods” made up of people you follow, people who follow you, people you frequently interact with, and people who are closely connected to those groups. They’re soft, probabilistic groupings rather than strict labels.

Everyone does not see the same replies. Bluesky is being a bit vague with “hidden.” Hidden means your reply is still anchored to the thread and can be expanded. There is another way Bluesky can handle this. Bluesky uses social neighborhoods to judge contextual relevance. Replies from people inside or near your social neighborhood are more likely to be shown inline with a thread, expanded by default, or served in feeds. Replies from outside your neighborhood are still public and still indexed, but they’re treated as lower-context contributions.

Basically, if you reply to a thread, you will see it anchored to the conversation, and everyone will see it in search results, as a hashtag, or from your profile, but it will not be accessible via the thread of the person you were replying to. It is like shadow-banning people from threads unless they are strongly networked.

Because people have not been working with the AT Protocol like I have, they assume they are shadow-banned across the entire Bluesky app view. No—everyone is automatically shadow-banned from everyone else unless they are within the same social neighborhood. In other words, you are not part of the conversation you think you are joining because you are not part of their social group.

Your replies will appear in profiles, hashtag feeds, or search results without being visually anchored to the full thread. Discovery impressions are neighborhood-agnostic: they serve content because it matches a query, tag, or activity stream. Once the reply is shown, the app then decides whether it’s worth pulling in the rest of the conversation for you. If the original author and most participants fall outside your neighborhood, Bluesky often chooses not to expand that context automatically.

Bluesky really is trying to avoid having to moderate, so this is their solution. Instead of banning or issuing takedown labels to DIDs, the system lets replies exist everywhere, but not in that particular instance of the thread.

I find this ironic because a large reason why many people are staying on Bluesky and not moving to the fediverse—thank God, because I do not want them there—is discoverability, virality, and engagement.

In case anyone is asking how I know so much about how these algorithms work: I was a consultant on a lot of these types of algorithms, so I certainly hope I’d know how they work, lol. No, you get no more details about the work I’ve done. I have no hand in the algorithm Bluesky is using, but I have proposed and implemented that type of algorithm before.

I have an interest in noetics and the noosphere. A large amount of my ontological work is an extension of my attempts to model domains that have no spatial or temporal coordinates. The question is how do you generalize a metric space that has no physically, spatial properties. I went to school to try to formalize those ideas. Turns out they’re rather useful for digital social networks, too. The ontological analog to spatial distance, when you have no space, is a graph of similarities.

This can be modeled by representing each item as a node in a weighted graph, where edges are weighted by dissimilarity rather than similarity. Highly similar items are connected by low-weight edges, while less similar items are connected by higher-weight edges. Distances in the graph, computed using standard shortest-path algorithms, then correspond to degrees of similarity. Closely related items are separated by short path lengths, while increasingly dissimilar items require longer paths through the graph. It turns out that attempts to generalize metric spaces for noetic domains—to model noetic/psychic spaces—are actually pretty useful for social media algorithms, lol.

BlueSky’s Solution To Moderating Is Moderating Without Moderating via Social Proximity

I have noticed a lot of people are confused about why some posts don’t show up on threads, though they are not labeled by the moderation layer. Bluesky has begun using what it calls social neighborhoods (or network proximity) as a ranking signal for replies in threads. Replies from people who are closer to you in the social graph, accounts you follow, interact with, or share mutual connections with, are prioritized and shown more prominently. Replies from accounts that are farther away in that network are down-ranked. They are pushed far down the thread or placed behind “hidden replies.”

Each person gets their own unique view of a thread based on their social graph. It creates the impression that replies from distant users simply don’t exist. This is true even though they’re still technically public and viewable if you expand the thread or adjust filters. Bluesky is explicitly using features of subgraphs to moderate without moderating. Their reasoning is that if you can’t see each other, you can’t harass each other. Ergo, there is nothing to moderate.

Bluesky mentions that here:

https://bsky.social/about/blog/10-31-2025-building-healthier-social-media-update

As a digression, I’m not going to lie: I really enjoyed working on software built on the AT protocol, but their fucking users are so goddamn weird. It’s sort of like enjoying building houses, but hating every single person who moves into them. But, you don’t have to deal with them because you’re just the contractor. That is how I feel about Bluesky. I hate the people. I really like the protocol and infrastructure.

I sort of am a sadist who does enjoy drama, so I do get schadenfreude from people with social media addictions and parasocial fixations who reply to random people on Bluesky, because they don’t realize their replies are disconnected from the author’s thread unless that person is within their network. They aren’t part of the conversation they think they are. They’re algorithmically isolated from everyone else. Their replies aren’t viewable from the author’s thread because of how Bluesky handles social neighborhoods.

Bluesky’s idea of social neighborhoods is about grouping users into overlapping clusters based on real interaction patterns rather than just the follow graph. Unlike Twitter, it does not treat the network as one big public square. Instead, it models networks of “social neighborhoods” made up of people you follow, people who follow you, people you frequently interact with, and people who are closely connected to those groups. They’re soft, probabilistic groupings rather than strict labels.

Everyone does not see the same replies. Bluesky is being a bit vague with “hidden.” Hidden means your reply is still anchored to the thread and can be expanded. There is another way Bluesky can handle this. Bluesky uses social neighborhoods to judge contextual relevance. Replies from people inside or near your social neighborhood are more likely to be shown inline with a thread, expanded by default, or served in feeds. Replies from outside your neighborhood are still public and still indexed, but they’re treated as lower-context contributions.

Basically, if you reply to a thread, you will see it anchored to the conversation, and everyone will see it in search results, as a hashtag, or from your profile, but it will not be accessible via the thread of the person you were replying to. It is like shadow-banning people from threads unless they are strongly networked.

Because people have not been working with the AT Protocol like I have, they assume they are shadow-banned across the entire Bluesky app view. No—everyone is automatically shadow-banned from everyone else unless they are within the same social neighborhood. In other words, you are not part of the conversation you think you are joining because you are not part of their social group.

Your replies will appear in profiles, hashtag feeds, or search results without being visually anchored to the full thread. Discovery impressions are neighborhood-agnostic: they serve content because it matches a query, tag, or activity stream. Once the reply is shown, the app then decides whether it’s worth pulling in the rest of the conversation for you. If the original author and most participants fall outside your neighborhood, Bluesky often chooses not to expand that context automatically.

Bluesky really is trying to avoid having to moderate, so this is their solution. Instead of banning or issuing takedown labels to DIDs, the system lets replies exist everywhere, but not in that particular instance of the thread.

I find this ironic because a large reason why many people are staying on Bluesky and not moving to the fediverse—thank God, because I do not want them there—is discoverability, virality, and engagement.

In case anyone is asking how I know so much about how these algorithms work: I was a consultant on a lot of these types of algorithms, so I certainly hope I’d know how they work, lol. No, you get no more details about the work I’ve done. I have no hand in the algorithm Bluesky is using, but I have proposed and implemented that type of algorithm before.

I have an interest in noetics and the noosphere. A large amount of my ontological work is an extension of my attempts to model domains that have no spatial or temporal coordinates. The question is how do you generalize a metric space that has no physically, spatial properties. I went to school to try to formalize those ideas. Turns out they’re rather useful for digital social networks, too. The ontological analog to spatial distance, when you have no space, is a graph of similarities.

This can be modeled by representing each item as a node in a weighted graph, where edges are weighted by dissimilarity rather than similarity. Highly similar items are connected by low-weight edges, while less similar items are connected by higher-weight edges. Distances in the graph, computed using standard shortest-path algorithms, then correspond to degrees of similarity. Closely related items are separated by short path lengths, while increasingly dissimilar items require longer paths through the graph. It turns out that attempts to generalize metric spaces for noetic domains—to model noetic/psychic spaces—are actually pretty useful for social media algorithms, lol.

Astroturfing Is Pretty Pointless When Social Subgraphs Are Fragmented (e.g., the Fediverse)

I am seeing astroturfing in the fediverse again, by AT Protocol developers implicitly trying to shill their products. I think it is stochastic behavior by developers with too much time on their hands. Honestly, I do not care. I like the people on ActivityPub more, but I like the AT Protocol better, and I have developed for both. Astroturfing on ActivityPub networks is fascinating to me because it is so pointless.

I am actually a Computational Biologist and Computer Scientist whose specialty is combinatorics, social graphs, graph theory, etc. Specifically, I use this to create epidemiological models for the memetic layer of human behaviors that act as vectors for diseases, using the SIRS model. I do not just study germs; I study human behaviors.

The models I construct extend into a “memetic layer,” in which beliefs, norms, and behaviors (such as risk-taking, compliance with public health measures, or susceptibility to misinformation) spread contagiously through social networks. These behaviors function as vectors that modulate biological transmission rates. As a result, the spread of ideas can accelerate, dampen, or reshape the spread of disease. By running computational simulations and agent-based models on these graphs, I study how network structure, influential nodes, clustering, and platform-specific dynamics affect behavioral contagion. I also examine how these factors influence epidemiological outcomes.

To say it very concisely, I study how the spread of bat-shit insane beliefs, shit posts, and memes influences whether or not there is a measles outbreak in Texas. Ironically, this is an evolution of my studying semiotics, memetics, and chaos magick in high school. I got a job where I can use occult, anarchist techniques professionally.

I think a large reason why I do not care about astroturfing in the fediverse is that it’s so pointless, lol. Astroturfing to manipulate the narrative would actually work better on Bluesky to keep people there than trying to recruit from the fediverse. Furthermore, big instances are relatively small. Some people on Bluesky have follower lists larger than an entire large instance in the fediverse.

Within ActivityPub networks, astroturfing rarely propagates far, because whether information spreads depends on properties of the social graph itself. Dense connectivity, short paths between communities, and a sufficient number of cross-cutting ties support diffusion. ActivityPub’s architecture tends to produce graphs that are fragmented and highly modular. This limits the reach of coordinated activity.

ActivityPub is a system where each instance maintains its own local user graph and exchanges activities through inboxes and outboxes. This makes it autonomous and decentralized. The network consists of loosely connected subgraphs. Cross-instance edges appear only through explicit follow relationships. The ActivityPub protocol does not provide a shared or complete view of the network. Measurements of the fediverse consistently show uneven connectivity between instances, clustering at the instance level, and relatively long effective path lengths across the network. Under these conditions, large cascades are uncommon.

Instance-level clustering means that in ActivityPub networks, users interact much more with others on the same server than with users on different servers. Because each instance has its own local timeline, culture, and moderation, connections form densely within instances and only sparsely across them through explicit follow relationships. This creates a network made up of tightly connected local communities linked by relatively few cross-instance ties, which slows the spread of information beyond its point of origin.

However, with the AT Protocol, global indexing and aggregation are explicitly supported. Relays and indexers can assemble near-complete views of the social graph. Applications built on top of this infrastructure operate over a graph that is denser and easier to traverse. There are fewer structural barriers between communities. The diffusion dynamics change substantially when content can move across the graph without relying on narrow federated paths.

Astroturfing depends on coordinated amplification, typically through tightly synchronized clusters of accounts intended to manufacture visibility. Work on coordinated inauthentic behavior shows that these tactics gain traction when they intersect highly connected regions of the graph or bridge otherwise separate communities. In networks with strong modularity, coordination remains local. ActivityPub’s federation model produces this kind of modularity by default. Coordinated clusters stand out clearly within instances. Their effects remain confined to those local neighborhoods.

Astroturfing on ActivityPub therefore tends to stall on its own because of the underlying graph topology. Without dense inter-instance connectivity or any form of global indexing, coordinated campaigns have a hard time moving beyond the immediate regions where they originate. Systems built on globally indexable social graphs, including those enabled by the AT Protocol, expose a much larger surface for viral spread. Network structure and connectivity account for the divergence where that is independent of moderation, cultural norms, ideology, or intent.

It’s just really funny to me how these stochastic techbro groups waste so many resources. I personally don’t want to go viral, which is why I avoid platforms where I can. The fact that it’s harder to achieve high virality on ActivityPub is exactly why I prefer the fediverse over the Atmosphere. One way to think about it is that you can change the ‘genetics’ of a system with a retrovirus, where memetic entities act as cultural retroviruses to reprogram the cultural loci of a space. That is their end goal. They are trying to hijack cultures memetically. You see this a lot with culture jamming.

Basically, the astroturfing on ActivityPub networks is designed to jam and subvert the culture. But, as I have already said, the topological structure makes memetic virality stall. They cannot achieve that kind of viral spread in the fediverse, which is why I cannot understand why they do this every year.

Astroturfing Is Pretty Pointless When Social Subgraphs Are Fragmented (e.g., the Fediverse)

I am seeing astroturfing in the fediverse again, by AT Protocol developers implicitly trying to shill their products. I think it is stochastic behavior by developers with too much time on their hands. Honestly, I do not care. I like the people on ActivityPub more, but I like the AT Protocol better, and I have developed for both. Astroturfing on ActivityPub networks is fascinating to me because it is so pointless.

I am actually a Computational Biologist and Computer Scientist whose specialty is combinatorics, social graphs, graph theory, etc. Specifically, I use this to create epidemiological models for the memetic layer of human behaviors that act as vectors for diseases, using the SIRS model. I do not just study germs; I study human behaviors.

The models I construct extend into a “memetic layer,” in which beliefs, norms, and behaviors (such as risk-taking, compliance with public health measures, or susceptibility to misinformation) spread contagiously through social networks. These behaviors function as vectors that modulate biological transmission rates. As a result, the spread of ideas can accelerate, dampen, or reshape the spread of disease. By running computational simulations and agent-based models on these graphs, I study how network structure, influential nodes, clustering, and platform-specific dynamics affect behavioral contagion. I also examine how these factors influence epidemiological outcomes.

To say it very concisely, I study how the spread of bat-shit insane beliefs, shit posts, and memes influences whether or not there is a measles outbreak in Texas. Ironically, this is an evolution of my studying semiotics, memetics, and chaos magick in high school. I got a job where I can use occult, anarchist techniques professionally.

I think a large reason why I do not care about astroturfing in the fediverse is that it’s so pointless, lol. Astroturfing to manipulate the narrative would actually work better on Bluesky to keep people there than trying to recruit from the fediverse. Furthermore, big instances are relatively small. Some people on Bluesky have follower lists larger than an entire large instance in the fediverse.

Within ActivityPub networks, astroturfing rarely propagates far, because whether information spreads depends on properties of the social graph itself. Dense connectivity, short paths between communities, and a sufficient number of cross-cutting ties support diffusion. ActivityPub’s architecture tends to produce graphs that are fragmented and highly modular. This limits the reach of coordinated activity.

ActivityPub is a system where each instance maintains its own local user graph and exchanges activities through inboxes and outboxes. This makes it autonomous and decentralized. The network consists of loosely connected subgraphs. Cross-instance edges appear only through explicit follow relationships. The ActivityPub protocol does not provide a shared or complete view of the network. Measurements of the fediverse consistently show uneven connectivity between instances, clustering at the instance level, and relatively long effective path lengths across the network. Under these conditions, large cascades are uncommon.

Instance-level clustering means that in ActivityPub networks, users interact much more with others on the same server than with users on different servers. Because each instance has its own local timeline, culture, and moderation, connections form densely within instances and only sparsely across them through explicit follow relationships. This creates a network made up of tightly connected local communities linked by relatively few cross-instance ties, which slows the spread of information beyond its point of origin.

However, with the AT Protocol, global indexing and aggregation are explicitly supported. Relays and indexers can assemble near-complete views of the social graph. Applications built on top of this infrastructure operate over a graph that is denser and easier to traverse. There are fewer structural barriers between communities. The diffusion dynamics change substantially when content can move across the graph without relying on narrow federated paths.

Astroturfing depends on coordinated amplification, typically through tightly synchronized clusters of accounts intended to manufacture visibility. Work on coordinated inauthentic behavior shows that these tactics gain traction when they intersect highly connected regions of the graph or bridge otherwise separate communities. In networks with strong modularity, coordination remains local. ActivityPub’s federation model produces this kind of modularity by default. Coordinated clusters stand out clearly within instances. Their effects remain confined to those local neighborhoods.

Astroturfing on ActivityPub therefore tends to stall on its own because of the underlying graph topology. Without dense inter-instance connectivity or any form of global indexing, coordinated campaigns have a hard time moving beyond the immediate regions where they originate. Systems built on globally indexable social graphs, including those enabled by the AT Protocol, expose a much larger surface for viral spread. Network structure and connectivity account for the divergence where that is independent of moderation, cultural norms, ideology, or intent.

It’s just really funny to me how these stochastic techbro groups waste so many resources. I personally don’t want to go viral, which is why I avoid platforms where I can. The fact that it’s harder to achieve high virality on ActivityPub is exactly why I prefer the fediverse over the Atmosphere. One way to think about it is that you can change the ‘genetics’ of a system with a retrovirus, where memetic entities act as cultural retroviruses to reprogram the cultural loci of a space. That is their end goal. They are trying to hijack cultures memetically. You see this a lot with culture jamming.

Basically, the astroturfing on ActivityPub networks is designed to jam and subvert the culture. But, as I have already said, the topological structure makes memetic virality stall. They cannot achieve that kind of viral spread in the fediverse, which is why I cannot understand why they do this every year.

Astroturfing Is Pretty Pointless When Social Subgraphs Are Fragmented (e.g., the Fediverse)

I am seeing astroturfing in the fediverse again, by AT Protocol developers implicitly trying to shill their products. I think it is stochastic behavior by developers with too much time on their hands. Honestly, I do not care. I like the people on ActivityPub more, but I like the AT Protocol better, and I have developed for both. Astroturfing on ActivityPub networks is fascinating to me because it is so pointless.

I am actually a Computational Biologist and Computer Scientist whose specialty is combinatorics, social graphs, graph theory, etc. Specifically, I use this to create epidemiological models for the memetic layer of human behaviors that act as vectors for diseases, using the SIRS model. I do not just study germs; I study human behaviors.

The models I construct extend into a “memetic layer,” in which beliefs, norms, and behaviors (such as risk-taking, compliance with public health measures, or susceptibility to misinformation) spread contagiously through social networks. These behaviors function as vectors that modulate biological transmission rates. As a result, the spread of ideas can accelerate, dampen, or reshape the spread of disease. By running computational simulations and agent-based models on these graphs, I study how network structure, influential nodes, clustering, and platform-specific dynamics affect behavioral contagion. I also examine how these factors influence epidemiological outcomes.

To say it very concisely, I study how the spread of bat-shit insane beliefs, shit posts, and memes influences whether or not there is a measles outbreak in Texas. Ironically, this is an evolution of my studying semiotics, memetics, and chaos magick in high school. I got a job where I can use occult, anarchist techniques professionally.

I think a large reason why I do not care about astroturfing in the fediverse is that it’s so pointless, lol. Astroturfing to manipulate the narrative would actually work better on Bluesky to keep people there than trying to recruit from the fediverse. Furthermore, big instances are relatively small. Some people on Bluesky have follower lists larger than an entire large instance in the fediverse.

Within ActivityPub networks, astroturfing rarely propagates far, because whether information spreads depends on properties of the social graph itself. Dense connectivity, short paths between communities, and a sufficient number of cross-cutting ties support diffusion. ActivityPub’s architecture tends to produce graphs that are fragmented and highly modular. This limits the reach of coordinated activity.

ActivityPub is a system where each instance maintains its own local user graph and exchanges activities through inboxes and outboxes. This makes it autonomous and decentralized. The network consists of loosely connected subgraphs. Cross-instance edges appear only through explicit follow relationships. The ActivityPub protocol does not provide a shared or complete view of the network. Measurements of the fediverse consistently show uneven connectivity between instances, clustering at the instance level, and relatively long effective path lengths across the network. Under these conditions, large cascades are uncommon.

Instance-level clustering means that in ActivityPub networks, users interact much more with others on the same server than with users on different servers. Because each instance has its own local timeline, culture, and moderation, connections form densely within instances and only sparsely across them through explicit follow relationships. This creates a network made up of tightly connected local communities linked by relatively few cross-instance ties, which slows the spread of information beyond its point of origin.

However, with the AT Protocol, global indexing and aggregation are explicitly supported. Relays and indexers can assemble near-complete views of the social graph. Applications built on top of this infrastructure operate over a graph that is denser and easier to traverse. There are fewer structural barriers between communities. The diffusion dynamics change substantially when content can move across the graph without relying on narrow federated paths.

Astroturfing depends on coordinated amplification, typically through tightly synchronized clusters of accounts intended to manufacture visibility. Work on coordinated inauthentic behavior shows that these tactics gain traction when they intersect highly connected regions of the graph or bridge otherwise separate communities. In networks with strong modularity, coordination remains local. ActivityPub’s federation model produces this kind of modularity by default. Coordinated clusters stand out clearly within instances. Their effects remain confined to those local neighborhoods.

Astroturfing on ActivityPub therefore tends to stall on its own because of the underlying graph topology. Without dense inter-instance connectivity or any form of global indexing, coordinated campaigns have a hard time moving beyond the immediate regions where they originate. Systems built on globally indexable social graphs, including those enabled by the AT Protocol, expose a much larger surface for viral spread. Network structure and connectivity account for the divergence where that is independent of moderation, cultural norms, ideology, or intent.

It’s just really funny to me how these stochastic techbro groups waste so many resources. I personally don’t want to go viral, which is why I avoid platforms where I can. The fact that it’s harder to achieve high virality on ActivityPub is exactly why I prefer the fediverse over the Atmosphere. One way to think about it is that you can change the ‘genetics’ of a system with a retrovirus, where memetic entities act as cultural retroviruses to reprogram the cultural loci of a space. That is their end goal. They are trying to hijack cultures memetically. You see this a lot with culture jamming.

Basically, the astroturfing on ActivityPub networks is designed to jam and subvert the culture. But, as I have already said, the topological structure makes memetic virality stall. They cannot achieve that kind of viral spread in the fediverse, which is why I cannot understand why they do this every year.

Astroturfing Is Pretty Pointless When Social Subgraphs Are Fragmented (e.g., the Fediverse)

I am seeing astroturfing in the fediverse again, by AT Protocol developers implicitly trying to shill their products. I think it is stochastic behavior by developers with too much time on their hands. Honestly, I do not care. I like the people on ActivityPub more, but I like the AT Protocol better, and I have developed for both. Astroturfing on ActivityPub networks is fascinating to me because it is so pointless.

I am actually a Computational Biologist and Computer Scientist whose specialty is combinatorics, social graphs, graph theory, etc. Specifically, I use this to create epidemiological models for the memetic layer of human behaviors that act as vectors for diseases, using the SIRS model. I do not just study germs; I study human behaviors.

The models I construct extend into a “memetic layer,” in which beliefs, norms, and behaviors (such as risk-taking, compliance with public health measures, or susceptibility to misinformation) spread contagiously through social networks. These behaviors function as vectors that modulate biological transmission rates. As a result, the spread of ideas can accelerate, dampen, or reshape the spread of disease. By running computational simulations and agent-based models on these graphs, I study how network structure, influential nodes, clustering, and platform-specific dynamics affect behavioral contagion. I also examine how these factors influence epidemiological outcomes.

To say it very concisely, I study how the spread of bat-shit insane beliefs, shit posts, and memes influences whether or not there is a measles outbreak in Texas. Ironically, this is an evolution of my studying semiotics, memetics, and chaos magick in high school. I got a job where I can use occult, anarchist techniques professionally.

I think a large reason why I do not care about astroturfing in the fediverse is that it’s so pointless, lol. Astroturfing to manipulate the narrative would actually work better on Bluesky to keep people there than trying to recruit from the fediverse. Furthermore, big instances are relatively small. Some people on Bluesky have follower lists larger than an entire large instance in the fediverse.

Within ActivityPub networks, astroturfing rarely propagates far, because whether information spreads depends on properties of the social graph itself. Dense connectivity, short paths between communities, and a sufficient number of cross-cutting ties support diffusion. ActivityPub’s architecture tends to produce graphs that are fragmented and highly modular. This limits the reach of coordinated activity.

ActivityPub is a system where each instance maintains its own local user graph and exchanges activities through inboxes and outboxes. This makes it autonomous and decentralized. The network consists of loosely connected subgraphs. Cross-instance edges appear only through explicit follow relationships. The ActivityPub protocol does not provide a shared or complete view of the network. Measurements of the fediverse consistently show uneven connectivity between instances, clustering at the instance level, and relatively long effective path lengths across the network. Under these conditions, large cascades are uncommon.

Instance-level clustering means that in ActivityPub networks, users interact much more with others on the same server than with users on different servers. Because each instance has its own local timeline, culture, and moderation, connections form densely within instances and only sparsely across them through explicit follow relationships. This creates a network made up of tightly connected local communities linked by relatively few cross-instance ties, which slows the spread of information beyond its point of origin.

However, with the AT Protocol, global indexing and aggregation are explicitly supported. Relays and indexers can assemble near-complete views of the social graph. Applications built on top of this infrastructure operate over a graph that is denser and easier to traverse. There are fewer structural barriers between communities. The diffusion dynamics change substantially when content can move across the graph without relying on narrow federated paths.

Astroturfing depends on coordinated amplification, typically through tightly synchronized clusters of accounts intended to manufacture visibility. Work on coordinated inauthentic behavior shows that these tactics gain traction when they intersect highly connected regions of the graph or bridge otherwise separate communities. In networks with strong modularity, coordination remains local. ActivityPub’s federation model produces this kind of modularity by default. Coordinated clusters stand out clearly within instances. Their effects remain confined to those local neighborhoods.

Astroturfing on ActivityPub therefore tends to stall on its own because of the underlying graph topology. Without dense inter-instance connectivity or any form of global indexing, coordinated campaigns have a hard time moving beyond the immediate regions where they originate. Systems built on globally indexable social graphs, including those enabled by the AT Protocol, expose a much larger surface for viral spread. Network structure and connectivity account for the divergence where that is independent of moderation, cultural norms, ideology, or intent.

It’s just really funny to me how these stochastic techbro groups waste so many resources. I personally don’t want to go viral, which is why I avoid platforms where I can. The fact that it’s harder to achieve high virality on ActivityPub is exactly why I prefer the fediverse over the Atmosphere. One way to think about it is that you can change the ‘genetics’ of a system with a retrovirus, where memetic entities act as cultural retroviruses to reprogram the cultural loci of a space. That is their end goal. They are trying to hijack cultures memetically. You see this a lot with culture jamming.

Basically, the astroturfing on ActivityPub networks is designed to jam and subvert the culture. But, as I have already said, the topological structure makes memetic virality stall. They cannot achieve that kind of viral spread in the fediverse, which is why I cannot understand why they do this every year.

I consider the divide between Continental and Analytical philosophy through my ontological lens after watching an IAI debate. I had already considered this as a use case, so the serendipity was convenient. What I used to call petulance, I now call ontological divide – and petulance. Thoughts?

https://brywillis634737.substack.com/p/who-decides-the-best-way-to-think

#philosophy #continental #analytic #ontology #communication #divide #iykyk #semantics #thinking #power #perspective #dialgue #dialectic #video #iai #blog #substack

News Flash: Fish Are Not Arboreal by Nature
🦈 https://philosophics.blog/2026/02/06/fish-are-not-arboreal-by-nature/?utm_source=masto&utm_medium=social
Those who know me know I am no fan of psychology as a discipline. A fundamental reason is the categorical misunderstanding of cognitive and precognitive functions.
#philosophy #psychology #ontology #selfhelp #mentalhealth #wellness #beliefs #salience #limits #architecture #society #culture #growth #suppression #repression #expression #regulation #reengineering #cognition #blog #podcast #communication

Astroturfing Is Pretty Pointless When Social Subgraphs Are Fragmented (e.g., the Fediverse)

I am seeing astroturfing in the fediverse again, by AT Protocol developers implicitly trying to shill their products. I think it is stochastic behavior by developers with too much time on their hands. Honestly, I do not care. I like the people on ActivityPub more, but I like the AT Protocol better, and I have developed for both. Astroturfing on ActivityPub networks is fascinating to me because it is so pointless.

I am actually a Computational Biologist and Computer Scientist whose specialty is combinatorics, social graphs, graph theory, etc. Specifically, I use this to create epidemiological models for the memetic layer of human behaviors that act as vectors for diseases, using the SIRS model. I do not just study germs; I study human behaviors.

The models I construct extend into a “memetic layer,” in which beliefs, norms, and behaviors (such as risk-taking, compliance with public health measures, or susceptibility to misinformation) spread contagiously through social networks. These behaviors function as vectors that modulate biological transmission rates. As a result, the spread of ideas can accelerate, dampen, or reshape the spread of disease. By running computational simulations and agent-based models on these graphs, I study how network structure, influential nodes, clustering, and platform-specific dynamics affect behavioral contagion. I also examine how these factors influence epidemiological outcomes.

To say it very concisely, I study how the spread of bat-shit insane beliefs, shit posts, and memes influences whether or not there is a measles outbreak in Texas. Ironically, this is an evolution of my studying semiotics, memetics, and chaos magick in high school. I got a job where I can use occult, anarchist techniques professionally.

I think a large reason why I do not care about astroturfing in the fediverse is that it’s so pointless, lol. Astroturfing to manipulate the narrative would actually work better on Bluesky to keep people there than trying to recruit from the fediverse. Furthermore, big instances are relatively small. Some people on Bluesky have follower lists larger than an entire large instance in the fediverse.

Within ActivityPub networks, astroturfing rarely propagates far, because whether information spreads depends on properties of the social graph itself. Dense connectivity, short paths between communities, and a sufficient number of cross-cutting ties support diffusion. ActivityPub’s architecture tends to produce graphs that are fragmented and highly modular. This limits the reach of coordinated activity.

ActivityPub is a system where each instance maintains its own local user graph and exchanges activities through inboxes and outboxes. This makes it autonomous and decentralized. The network consists of loosely connected subgraphs. Cross-instance edges appear only through explicit follow relationships. The ActivityPub protocol does not provide a shared or complete view of the network. Measurements of the fediverse consistently show uneven connectivity between instances, clustering at the instance level, and relatively long effective path lengths across the network. Under these conditions, large cascades are uncommon.

Instance-level clustering means that in ActivityPub networks, users interact much more with others on the same server than with users on different servers. Because each instance has its own local timeline, culture, and moderation, connections form densely within instances and only sparsely across them through explicit follow relationships. This creates a network made up of tightly connected local communities linked by relatively few cross-instance ties, which slows the spread of information beyond its point of origin.

However, with the AT Protocol, global indexing and aggregation are explicitly supported. Relays and indexers can assemble near-complete views of the social graph. Applications built on top of this infrastructure operate over a graph that is denser and easier to traverse. There are fewer structural barriers between communities. The diffusion dynamics change substantially when content can move across the graph without relying on narrow federated paths.

Astroturfing depends on coordinated amplification, typically through tightly synchronized clusters of accounts intended to manufacture visibility. Work on coordinated inauthentic behavior shows that these tactics gain traction when they intersect highly connected regions of the graph or bridge otherwise separate communities. In networks with strong modularity, coordination remains local. ActivityPub’s federation model produces this kind of modularity by default. Coordinated clusters stand out clearly within instances. Their effects remain confined to those local neighborhoods.

Astroturfing on ActivityPub therefore tends to stall on its own because of the underlying graph topology. Without dense inter-instance connectivity or any form of global indexing, coordinated campaigns have a hard time moving beyond the immediate regions where they originate. Systems built on globally indexable social graphs, including those enabled by the AT Protocol, expose a much larger surface for viral spread. Network structure and connectivity account for the divergence where that is independent of moderation, cultural norms, ideology, or intent.

It’s just really funny to me how these stochastic techbro groups waste so many resources. I personally don’t want to go viral, which is why I avoid platforms where I can. The fact that it’s harder to achieve high virality on ActivityPub is exactly why I prefer the fediverse over the Atmosphere. One way to think about it is that you can change the ‘genetics’ of a system with a retrovirus, where memetic entities act as cultural retroviruses to reprogram the cultural loci of a space. That is their end goal. They are trying to hijack cultures memetically. You see this a lot with culture jamming.

Basically, the astroturfing on ActivityPub networks is designed to jam and subvert the culture. But, as I have already said, the topological structure makes memetic virality stall. They cannot achieve that kind of viral spread in the fediverse, which is why I cannot understand why they do this every year.

Astroturfing Is Pretty Pointless When Social Subgraphs Are Fragmented (e.g., the Fediverse)

I am seeing astroturfing in the fediverse again, by AT Protocol developers implicitly trying to shill their products. I think it is stochastic behavior by developers with too much time on their hands. Honestly, I do not care. I like the people on ActivityPub more, but I like the AT Protocol better, and I have developed for both. Astroturfing on ActivityPub networks is fascinating to me because it is so pointless.

I am actually a Computational Biologist and Computer Scientist whose specialty is combinatorics, social graphs, graph theory, etc. Specifically, I use this to create epidemiological models for the memetic layer of human behaviors that act as vectors for diseases, using the SIRS model. I do not just study germs; I study human behaviors.

The models I construct extend into a “memetic layer,” in which beliefs, norms, and behaviors (such as risk-taking, compliance with public health measures, or susceptibility to misinformation) spread contagiously through social networks. These behaviors function as vectors that modulate biological transmission rates. As a result, the spread of ideas can accelerate, dampen, or reshape the spread of disease. By running computational simulations and agent-based models on these graphs, I study how network structure, influential nodes, clustering, and platform-specific dynamics affect behavioral contagion. I also examine how these factors influence epidemiological outcomes.

To say it very concisely, I study how the spread of bat-shit insane beliefs, shit posts, and memes influences whether or not there is a measles outbreak in Texas. Ironically, this is an evolution of my studying semiotics, memetics, and chaos magick in high school. I got a job where I can use occult, anarchist techniques professionally.

I think a large reason why I do not care about astroturfing in the fediverse is that it’s so pointless, lol. Astroturfing to manipulate the narrative would actually work better on Bluesky to keep people there than trying to recruit from the fediverse. Furthermore, big instances are relatively small. Some people on Bluesky have follower lists larger than an entire large instance in the fediverse.

Within ActivityPub networks, astroturfing rarely propagates far, because whether information spreads depends on properties of the social graph itself. Dense connectivity, short paths between communities, and a sufficient number of cross-cutting ties support diffusion. ActivityPub’s architecture tends to produce graphs that are fragmented and highly modular. This limits the reach of coordinated activity.

ActivityPub is a system where each instance maintains its own local user graph and exchanges activities through inboxes and outboxes. This makes it autonomous and decentralized. The network consists of loosely connected subgraphs. Cross-instance edges appear only through explicit follow relationships. The ActivityPub protocol does not provide a shared or complete view of the network. Measurements of the fediverse consistently show uneven connectivity between instances, clustering at the instance level, and relatively long effective path lengths across the network. Under these conditions, large cascades are uncommon.

Instance-level clustering means that in ActivityPub networks, users interact much more with others on the same server than with users on different servers. Because each instance has its own local timeline, culture, and moderation, connections form densely within instances and only sparsely across them through explicit follow relationships. This creates a network made up of tightly connected local communities linked by relatively few cross-instance ties, which slows the spread of information beyond its point of origin.

However, with the AT Protocol, global indexing and aggregation are explicitly supported. Relays and indexers can assemble near-complete views of the social graph. Applications built on top of this infrastructure operate over a graph that is denser and easier to traverse. There are fewer structural barriers between communities. The diffusion dynamics change substantially when content can move across the graph without relying on narrow federated paths.

Astroturfing depends on coordinated amplification, typically through tightly synchronized clusters of accounts intended to manufacture visibility. Work on coordinated inauthentic behavior shows that these tactics gain traction when they intersect highly connected regions of the graph or bridge otherwise separate communities. In networks with strong modularity, coordination remains local. ActivityPub’s federation model produces this kind of modularity by default. Coordinated clusters stand out clearly within instances. Their effects remain confined to those local neighborhoods.

Astroturfing on ActivityPub therefore tends to stall on its own because of the underlying graph topology. Without dense inter-instance connectivity or any form of global indexing, coordinated campaigns have a hard time moving beyond the immediate regions where they originate. Systems built on globally indexable social graphs, including those enabled by the AT Protocol, expose a much larger surface for viral spread. Network structure and connectivity account for the divergence where that is independent of moderation, cultural norms, ideology, or intent.

It’s just really funny to me how these stochastic techbro groups waste so many resources. I personally don’t want to go viral, which is why I avoid platforms where I can. The fact that it’s harder to achieve high virality on ActivityPub is exactly why I prefer the fediverse over the Atmosphere. One way to think about it is that you can change the ‘genetics’ of a system with a retrovirus, where memetic entities act as cultural retroviruses to reprogram the cultural loci of a space. That is their end goal. They are trying to hijack cultures memetically. You see this a lot with culture jamming.

Basically, the astroturfing on ActivityPub networks is designed to jam and subvert the culture. But, as I have already said, the topological structure makes memetic virality stall. They cannot achieve that kind of viral spread in the fediverse, which is why I cannot understand why they do this every year.

#Kant - 'Transcendental Idealism'

"Are Space and Time all in your Mind?"

https://www.youtube.com/watch?v=JZEhrABp2wQ&ab_channel=PhilosophyVibe

#ImmanuelKant #Space #Time #SpaceTime #TranscendentalIdealism #Metaphysics #Idealism #Realism #IndirectRealism #Mind #TheMind #Peerception #Ontology #Noumenon #Noumena #Noumenal #Phenomenon #Phenomena #Phenomenal #Phenomenology