#astroturf — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #astroturf, aggregated by home.social.
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“Israeli Paper Admits That The Mossad Astroturfed The January Riots In Iran”
by The Dissident on Substack
@[email protected]
@[email protected]
@[email protected]
@iran
@BBC5Live
@BBCRadio4
@BBCNews
@guardian
@Independent
@thetimes
@newyorktimes
@miamiherald“The Israeli paper Ynet put the final nail in the coffin of the CIA/Mossad narrative in Iran, admitting that the Israeli Mossad laid the groundwork for the violent riots that preceded the Israeli/American war, and which were presented in the mainstream media as organic peaceful protests”
https://open.substack.com/pub/the307/p/israeli-paper-admits-that-the-mossad
#Press #SocialMedia #Iran #War #Trump #Israel #OperationEpsteinFury #OperationEpicMistake #RegimeChange #WarCrimes #CrimesAgainstHumanity #Hormuz #Empire #Collapse #US #Mossad #CIA #Astroturf #Riots
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*It's a *Chinese* bamboo-plastic, so maybe there's some kind of bamboo privacy-threat involved, that A16Z and Palantir could pay to raise a big MAGA stink about #grassroots #astroturf
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*It's a *Chinese* bamboo-plastic, so maybe there's some kind of bamboo privacy-threat involved, that A16Z and Palantir could pay to raise a big MAGA stink about #grassroots #astroturf
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*It's a *Chinese* bamboo-plastic, so maybe there's some kind of bamboo privacy-threat involved, that A16Z and Palantir could pay to raise a big MAGA stink about #grassroots #astroturf
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*It's a *Chinese* bamboo-plastic, so maybe there's some kind of bamboo privacy-threat involved, that A16Z and Palantir could pay to raise a big MAGA stink about #grassroots #astroturf
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金沢で戦争反対デモ、ネットで嘲笑と批判の声
さいたま市水道局のメーター盗難防止メールが住民反発を呼ぶ
フィフィのサンミュージック公式プロフィール削除 帰化取り消し発言の影響か
石破茂氏、拉致解決へ連絡事務所構想に再び意欲辺野古警備員死亡事故、事故2日前安全対策却下が判明
#botFarm #clickFarm #スマホ農場 #OSINT #Japan
from tech view, #X #Twitter #Japan inside can see manipulation in details but, ignore #astroTurf
https://www.youtube.com/watch?v=p84OsDn_LPE&feature=youtu.be [参照] -
Gardeners told not to install artificial grass in garden for stark reason https://www.allforgardening.com/1734128/gardeners-told-not-to-install-artificial-grass-in-garden-for-stark-reason/ #ArtificalGrass #astroturf #garden #gardening #IsAstroturfBad #Mowing #ShouldIGetArtificialGrass #ShouldIGetAstroturf #Weeding
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Gardeners told not to install artificial grass in garden for stark reason https://www.allforgardening.com/1734128/gardeners-told-not-to-install-artificial-grass-in-garden-for-stark-reason/ #ArtificalGrass #astroturf #garden #gardening #IsAstroturfBad #Mowing #ShouldIGetArtificialGrass #ShouldIGetAstroturf #Weeding
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Dutch YouTube creators behind Alberta separatist videos getting millions of views
Albertans end up bombarded with targeted messaging that amounts to Propaganda or Slopaganda, funded by dark money.
This week, a report by the Media Ecosystem Observatory (MEO), a joint project between the University of Toronto and McGill University in Montreal looking into Canadian media, identified 20 YouTube channels as part of a co-ordinated network focused on separatism in western Canadian provinces, and other political issues.
The report noted they use near-identical scripts and dubbed them “slopaganda.”
Altogether, the accounts have garnered roughly 40 million views.
The report says many of the videos contain “frequent and obvious lies, drawing on real news stories to reach exaggerated conclusions designed to exploit political divisions.” The report did not identify the individuals behind the apparent network, citing a lack of “identifying information to real humans or organizations nor ties to the secession movement in Alberta.”
“I think it’s disturbing that these voices are able to insert themselves in the conversation, and their interest is not to further the democratic discourse or … have a healthy, authentic conversation,” said Chris Ross, a senior analyst at the Media Ecosystem Observatory.
“They’re putting themselves in the middle of that, misleading Albertans, Canadians, and they’re just doing it to make money.”
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堀江貴文氏「キャバクラ論争」に痛烈「不細工な嫁と結婚するしかなかった非モテオタク達が…」
#botFarm #clickFarm #OSINT #astroTurf #astroTurfing
#attentionEconomy #Japanese#ElonMusk
✨ #Japan is a great country ( to suck up money )✨#TakafumiHorie #Hiroyuki #Epstein #JoiIto #MIT
https://youtube.com/shorts/OGjltlOCEWM?feature=share [参照] -
#Hatred #ForYou #X #Twitter #Japan
児童手当の誤支給、外国人出国後も約350自治体で経験あり京都南丹市小6女児殺害事件 養父が逮捕・殺害認める
京都高麗寺土葬墓地拡張に懸念広がるも寺側は許可済みと説明
立川市で陸上自衛隊追放を訴えるデモが発生し警察が参加者を点字ブロック上に誘導
産経FNN合同世論調査で高市早苗内閣支持率70.2%に回復し憲法への自衛隊明記賛成59.3%
産経FNN合同世論調査で高市早苗内閣支持率70.2％に回復自衛隊明記賛成59.3％
#astroTurfing #Japan #OSINT #astroTurf #Takaichi -
オトイケ
@otonanoikenga
【悲報】高市総理、現状言い返せる部分無し…神谷宗幣「国民に謝れよ！」
一言だけでも…どうすか…
https://www.youtube.com/shorts/yeKKDU2qezs?feature=share#Takaichi #SanaeTakaichi #ShinzoAbe #UnificationChurch
#Trump #Epstein #ElonMusk #X #Twitter #botFarm #clickFarm #astroTurf
#オトイケ
#@otonanoikenga
https://x.com/otonanoikenga/status/2045769603868209253?s=20 -
#Japanese #SocialMedia #Hatred control
https://www.youtube.com/watch?v=iwzPOPSDYmg&feature=youtu.be
いちか
@nBwQSzmg3qU2ysd
これが今の池袋です😨#いちか
#@nBwQSzmg3qU2ysd#botFarm #clickFarm #astroTurf #astroTurfing #Japan #OSINT #ElonMusk #X #Twitter
#Trump #Epstein #Iran #Israel #Paletine #gaza #Ukraine #Venezuela
#OSINT
https://x.com/nBwQSzmg3qU2ysd/status/2046028200120324199?s=20 -
#PlasticPatrol: the #CitizenScientists tackling #litter in #Australian #waterways
#Plastics make up the majority of litter across the country. In the absence of regulation, the public are taking matters into their own hands
by James Norman, Fri 30 Jan 2026
"Neil Blake weighs a paper bag of fake grass fragments he has collected from a stormwater gutter near #DarebinCreek in #Melbourne’s north.
"Over the past three years Blake has conducted 56 collections of synthetic turf in the waterway alongside the KP Hardiman Reserve hockey pitch.
" 'I noticed that a local hockey pitch was being replaced and the plastic surface was running off into the local environment,' he says. Strong northerly winds and #LeafBlowers had helped shed the turf fragments into the local #environment.
"In addition to impacts on #AquaticEcosystems, scientific analysis suggests #PlasticPollution is exacerbating #ClimateChange, #biodiversity loss and #OceanAcidification.
"Australians produce more than 3m tonnes of plastic waste each year, and according to Clean Up’s annual survey of parks, beaches, creeks and other public spaces, plastics make up more than 80% of litter across the country. A review by the New South Wales chief scientist found that one #SyntheticTurf field could transport between 10kg and 100kg of plastic fragments into the #stormwater system or local waterways.
"Blake has taken advantage of the electronic scales provided by the newly opened community science laboratory in the Port Phillip #EcoCentre in #StKilda, to quantify his samples to present to the local council and the Environment Protection Authority. The lab hosts facilities including microscopes, measuring equipment, safety gear and access to advice from trained scientists.
"It’s one example of citizen scientists tackling the growing problem of plastics in #waterways, including #beaches, #rivers and dive sites around the country."
Archived version:
https://archive.ph/okVtk#SolarPunkSunday #LitterCleanup #NewSouthWales #Australia #PlasticTurf #PlasticPollution #CitizenScience #WaterIsLife #Astroturf #PlasticPollution #Microplastics
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#PlasticPatrol: the #CitizenScientists tackling #litter in #Australian #waterways
#Plastics make up the majority of litter across the country. In the absence of regulation, the public are taking matters into their own hands
by James Norman, Fri 30 Jan 2026
"Neil Blake weighs a paper bag of fake grass fragments he has collected from a stormwater gutter near #DarebinCreek in #Melbourne’s north.
"Over the past three years Blake has conducted 56 collections of synthetic turf in the waterway alongside the KP Hardiman Reserve hockey pitch.
" 'I noticed that a local hockey pitch was being replaced and the plastic surface was running off into the local environment,' he says. Strong northerly winds and #LeafBlowers had helped shed the turf fragments into the local #environment.
"In addition to impacts on #AquaticEcosystems, scientific analysis suggests #PlasticPollution is exacerbating #ClimateChange, #biodiversity loss and #OceanAcidification.
"Australians produce more than 3m tonnes of plastic waste each year, and according to Clean Up’s annual survey of parks, beaches, creeks and other public spaces, plastics make up more than 80% of litter across the country. A review by the New South Wales chief scientist found that one #SyntheticTurf field could transport between 10kg and 100kg of plastic fragments into the #stormwater system or local waterways.
"Blake has taken advantage of the electronic scales provided by the newly opened community science laboratory in the Port Phillip #EcoCentre in #StKilda, to quantify his samples to present to the local council and the Environment Protection Authority. The lab hosts facilities including microscopes, measuring equipment, safety gear and access to advice from trained scientists.
"It’s one example of citizen scientists tackling the growing problem of plastics in #waterways, including #beaches, #rivers and dive sites around the country."
Archived version:
https://archive.ph/okVtk#SolarPunkSunday #LitterCleanup #NewSouthWales #Australia #PlasticTurf #PlasticPollution #CitizenScience #WaterIsLife #Astroturf #PlasticPollution #Microplastics
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#PlasticPatrol: the #CitizenScientists tackling #litter in #Australian #waterways
#Plastics make up the majority of litter across the country. In the absence of regulation, the public are taking matters into their own hands
by James Norman, Fri 30 Jan 2026
"Neil Blake weighs a paper bag of fake grass fragments he has collected from a stormwater gutter near #DarebinCreek in #Melbourne’s north.
"Over the past three years Blake has conducted 56 collections of synthetic turf in the waterway alongside the KP Hardiman Reserve hockey pitch.
" 'I noticed that a local hockey pitch was being replaced and the plastic surface was running off into the local environment,' he says. Strong northerly winds and #LeafBlowers had helped shed the turf fragments into the local #environment.
"In addition to impacts on #AquaticEcosystems, scientific analysis suggests #PlasticPollution is exacerbating #ClimateChange, #biodiversity loss and #OceanAcidification.
"Australians produce more than 3m tonnes of plastic waste each year, and according to Clean Up’s annual survey of parks, beaches, creeks and other public spaces, plastics make up more than 80% of litter across the country. A review by the New South Wales chief scientist found that one #SyntheticTurf field could transport between 10kg and 100kg of plastic fragments into the #stormwater system or local waterways.
"Blake has taken advantage of the electronic scales provided by the newly opened community science laboratory in the Port Phillip #EcoCentre in #StKilda, to quantify his samples to present to the local council and the Environment Protection Authority. The lab hosts facilities including microscopes, measuring equipment, safety gear and access to advice from trained scientists.
"It’s one example of citizen scientists tackling the growing problem of plastics in #waterways, including #beaches, #rivers and dive sites around the country."
Archived version:
https://archive.ph/okVtk#SolarPunkSunday #LitterCleanup #NewSouthWales #Australia #PlasticTurf #PlasticPollution #CitizenScience #WaterIsLife #Astroturf #PlasticPollution #Microplastics
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#PlasticPatrol: the #CitizenScientists tackling #litter in #Australian #waterways
#Plastics make up the majority of litter across the country. In the absence of regulation, the public are taking matters into their own hands
by James Norman, Fri 30 Jan 2026
"Neil Blake weighs a paper bag of fake grass fragments he has collected from a stormwater gutter near #DarebinCreek in #Melbourne’s north.
"Over the past three years Blake has conducted 56 collections of synthetic turf in the waterway alongside the KP Hardiman Reserve hockey pitch.
" 'I noticed that a local hockey pitch was being replaced and the plastic surface was running off into the local environment,' he says. Strong northerly winds and #LeafBlowers had helped shed the turf fragments into the local #environment.
"In addition to impacts on #AquaticEcosystems, scientific analysis suggests #PlasticPollution is exacerbating #ClimateChange, #biodiversity loss and #OceanAcidification.
"Australians produce more than 3m tonnes of plastic waste each year, and according to Clean Up’s annual survey of parks, beaches, creeks and other public spaces, plastics make up more than 80% of litter across the country. A review by the New South Wales chief scientist found that one #SyntheticTurf field could transport between 10kg and 100kg of plastic fragments into the #stormwater system or local waterways.
"Blake has taken advantage of the electronic scales provided by the newly opened community science laboratory in the Port Phillip #EcoCentre in #StKilda, to quantify his samples to present to the local council and the Environment Protection Authority. The lab hosts facilities including microscopes, measuring equipment, safety gear and access to advice from trained scientists.
"It’s one example of citizen scientists tackling the growing problem of plastics in #waterways, including #beaches, #rivers and dive sites around the country."
Archived version:
https://archive.ph/okVtk#SolarPunkSunday #LitterCleanup #NewSouthWales #Australia #PlasticTurf #PlasticPollution #CitizenScience #WaterIsLife #Astroturf #PlasticPollution #Microplastics
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#PlasticPatrol: the #CitizenScientists tackling #litter in #Australian #waterways
#Plastics make up the majority of litter across the country. In the absence of regulation, the public are taking matters into their own hands
by James Norman, Fri 30 Jan 2026
"Neil Blake weighs a paper bag of fake grass fragments he has collected from a stormwater gutter near #DarebinCreek in #Melbourne’s north.
"Over the past three years Blake has conducted 56 collections of synthetic turf in the waterway alongside the KP Hardiman Reserve hockey pitch.
" 'I noticed that a local hockey pitch was being replaced and the plastic surface was running off into the local environment,' he says. Strong northerly winds and #LeafBlowers had helped shed the turf fragments into the local #environment.
"In addition to impacts on #AquaticEcosystems, scientific analysis suggests #PlasticPollution is exacerbating #ClimateChange, #biodiversity loss and #OceanAcidification.
"Australians produce more than 3m tonnes of plastic waste each year, and according to Clean Up’s annual survey of parks, beaches, creeks and other public spaces, plastics make up more than 80% of litter across the country. A review by the New South Wales chief scientist found that one #SyntheticTurf field could transport between 10kg and 100kg of plastic fragments into the #stormwater system or local waterways.
"Blake has taken advantage of the electronic scales provided by the newly opened community science laboratory in the Port Phillip #EcoCentre in #StKilda, to quantify his samples to present to the local council and the Environment Protection Authority. The lab hosts facilities including microscopes, measuring equipment, safety gear and access to advice from trained scientists.
"It’s one example of citizen scientists tackling the growing problem of plastics in #waterways, including #beaches, #rivers and dive sites around the country."
Archived version:
https://archive.ph/okVtk#SolarPunkSunday #LitterCleanup #NewSouthWales #Australia #PlasticTurf #PlasticPollution #CitizenScience #WaterIsLife #Astroturf #PlasticPollution #Microplastics
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#News #Japan #X #Twitter
辺野古テントの献花扱いが物議、取材後バケツ放置の写真拡散韓国海賊版サイト元運営者の日本帰化で制度改革求める声広がる
BBC動画きっかけで日本の空き家を外国人が積極購入か
#astroTurf #astroTurfing #OSINT #Japanese #botFarm #ClickFarm
#ElonMusk
Great Country! ( easy )#SanaeTakaichi #ShinzoAbe
https://youtube.com/shorts/-qkGsCv7-O0?feature=share -
サンモニ膳場貴子「報道が過熱してデマ情報も拡散」京都男児遺棄事件めぐり問題提起
https://www.youtube.com/watch?v=iwzPOPSDYmg&feature=youtu.be
#botFarm #clickFarm #astroTurfing #astroTurf
#サンデーモーニング #サンモニ #SundayMorning #Japan #OSINT
#Trump #ElonMusk #Israel
Super Great！#Palestine #gaza #Ukraine #Vanazuela
#日韓スポーツ
https://www.nikkansports.com/entertainment/news/202604190000239.html -
いちか
@nBwQSzmg3qU2ysdおい！マジで何だよこれ！！！
890万人もアンダークラスが苦しんでんのに、外国人労働者ばっか騒いでる場合かよ💢
年収216万で貧困率37%超えて、結婚も子育ても諦めざるを得ない日本人がこんなにいるのに😖
これを放置して「外国人増やせば解決〜」とかふざけんな‼️💢
#いちか
#@nBwQSzmg3qU2ysd
#astroTurfing #astroTurf #botFarm #clickFarm #OSINT #Japan #X #Twitter
https://youtube.com/shorts/XmiNnDX29Aw?feature=share -
#高橋洋一
日本はとっくにイラン産原油の輸入を停止しているのに、イランが日本に原油を出さないことになるかもしれない✨
#YoichiTakahashi#竹中平蔵 #HeizoTakenaka #Trump #Epstein #ElonMusk
#Iran #Ukraine #Venezuela#Takaichi #SanaeTakaichi #TaroAso #ShinzoAbe
#botFarm #clickFarm #socialMedia #X #Twitter #YouTube
#astroTurf #astroturfinghttps://www.youtube.com/watch?v=cWhO0RVeu3Q&feature=youtu.be
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ひで2022真実を追求
@hide_Q_追記：結婚で姓が変わったわけじゃない。
パキスタン国籍のまま、通名だけ使ってるだけ。
なのに『川崎容疑者』連呼って…これ報道として成立してる？
マスゴミの洗脳工作、そろそろ限界だろ。#Japan #astroTurfing #astroTurf #botFarm #clickFarm #OSINT #X #Twitter #Pakistan #Trump #Iran
#ElonMusk
✨Let it go✨～🎵 I am the one on #SocialMedia God✨ -
ひで2022真実を追求
@hide_Q_このニュースヤバくない？
アナウンサーが何度も何度も「川崎容疑者」「川崎容疑者」って連呼してるんだけど、
本名はモハマッドアリ（パキスタン国籍24歳）だよね？#Japan #astroTurfing #astroTurf #botFarm #clickFarm #OSINT #X #Twitter #Pakistan #Trump #Iran
#ElonMusk
✨Let it go✨https://www.youtube.com/watch?si=6_jetG-tAvwcZDiM&v=iwzPOPSDYmg&feature=youtu.be
#ひで2022真実を追求
#@hide_Q_ -
ひで2022真実を追求
@hide_Q_このニュースヤバくない？
アナウンサーが何度も何度も「川崎容疑者」「川崎容疑者」って連呼してるんだけど、
本名はモハマッドアリ（パキスタン国籍24歳）だよね？#Japan #astroTurfing #astroTurf #botFarm #clickFarm #OSINT #X #Twitter #Pakistan #Trump #Iran
#ElonMusk
✨Let it go✨
https://www.youtube.com/watch?si=6_jetG-tAvwcZDiM&v=iwzPOPSDYmg&feature=youtu.be#ひで2022真実を追求
#@hide_Q_ -
Do you seriously see this is natural, organic?
#Twitter #Japan #OSINT
#botFarm #clickFarm#Japanese
#ElonMusk let #astroTurf X freelyFrench headquarters of Elon Musk’s X raided by Paris cybercrime unit
Prosecutors’ announcement comes amid a hardening of European attitudes to social media firms [参照] -
So, I am a Computational Biologist. Keep that in mind. I’m an actual scientist who works with ecological concepts, specifically the microbiome. One of the most insufferable reactions to the cyberpunk era we inhabit is the emergence of anti-science ideas from the left in response to techno-fascism. The strange part is that many people on the left do not even recognize them as anti-science, because they assume the left is aligned with science and the right opposed to it; ergo, if the left says it, it must be scientific. It is insane: washing your hands is technology. Medicine is technology.
I think, because the Internet has hijacked people’s brains, many conflate technology with electronics or machines. Anthropologically, technology consists of material objects, techniques, and organized practices through which humans intentionally intervene in their environments. Technology is culture, and human culture is technology. When someone learns a skill or a discipline from someone else, that is an extension of technology.
Technology encompasses craft traditions (blacksmithing), agriculture, and institutionalized processes of teaching and learning. Agriculture is one of the oldest forms of technology. Yes, farmers are tech workers. I write code, but I also spent a large amount of time on a farm, and I can tell you that many tech workers who pride themselves on writing code would not know what to do with farm equipment.
So, from that broad perspective, we can sum technology up in one word: education. A basic heuristic for determining if something is cultural or not is: can it be taught and learned? These words? I was taught English, and I am using an invented language to transmit knowledge to you; ergo, I am using technology to transmit cultural knowledge to you. Reading a book is thus using a piece of human technology. So, being anti-tech connotes being anti-education.
What got me thinking about this is a toot I read on Mastodon:
The truth is that society needs to develop ethically and ecologically more than it does technologically. That’s not to say that we should shun technology, but our development along other lines lags far behind our technological capacity.
Sounds valid, right? That is the distinct smell of bull shit.This is a clear example of what is called a platitude. Platitudes are memetically hijacking people’s brains. Memetics actually hijack your brain—they change it. It’s similar to how a retrovirus can alter the genome of its host. So, trying to have conversations with these people is pointless, which is why I avoid the chronically online Internet scene and arguing with them.
It made me want to scream. As I mentioned earlier, technology is basically a set of things you learn from other humans—typically within a culture—that helps you do or make something. You know what else is learned within human society? A normative set of cultural values about how we ought to behave. So, both technology and culture emerge from the same thing simultaneously and mutually. You cannot have humans intervening in things to achieve ecological development, because that is technology, and you cannot educate humans on ethics without an invented language. It is literally an anti-education argument.
Ethics and technology arise together from the same human conditions and social processes. It makes little sense to claim that technology is “outpacing” ethics. The two do not develop independently. We form ethical norms in response to new capacities and circumstances. There would be no cultural norms about how to use the Internet if the Internet did not exist. And, there would be no ethical debates about AI if AI did not exist. Ethical reflection emerges alongside technological change because both are products of human culture.
As new problems create new technologies that create new problems, societies respond by negotiating norms, rules, and expectations appropriate to those contexts. The same pattern appears in politics. Politics concerns who gets what, when, and how—it is the negotiation of power, rights, and resources. Without resources or competing claims, there would be nothing to negotiate. Ethics and politics are not trailing behind technology because they are co-emergent responses to the same underlying realities.
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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.
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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.
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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.
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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.
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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.
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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.
-
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.
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The Truth About Social Media Manipulation, #Japan too
#Japanese #astroTurf go exactly the same way
#TaroAso imperial Japan grand son n
#Takaichi recommends #Nati #Hitler #Election #Strategy#Nazis understood how much media is important and had all control
#OSINT #SocialMedia
https://www.youtube.com/watch?v=OfVHvTBGYyA&feature=youtu.be -
髙橋𝕏羚@闇を暴く人。
@Parsonalsecret
また中国人の遭難者なんと今年に入ってからのレスキューの９割は外国人で中国人ばかり
隊員も命懸けでレスキューしているのに費用は我々の税金
これは本人からしっかりと徴収して下さい
#astroTurf #OSINT free #Japanese X/ #Twitter #clickFarm #botFarm #ステマ ステルスマーケティング #Hitler 選挙戦略 #Nazi
厳冬の日本で外国人バックカントリー遭難相次ぐ 税金負担に実費請求の声
北海道や新潟、富士山などで外国人観光客のバックカントリースキーや無謀登山による遭難が続いています。
1月上旬の北海道では29件中26件が外国人
中国人観光客の事例が目立ちXでは救助費用の公費負担に不満の声が広がり、実費請求を求める意見が数千の反応
中国大使館もコース外滑走を避けるよう異例の注意喚起を発信
https://x.com/Parsonalsecret/status/2016442914554130706?s=20 -
Bluesky is An Ontological Space for Sadomasochism, Trolling, & Schadenfreude
So, during the initial exodus from Twitter after it became X following Elon Musk’s purchase, many people left but kept their accounts, purposefully to bully, surveil, antagonize, and troll others. People—including me—moved to Bluesky, Mastodon, or both, and used their Twitter accounts purely for harassment and similar behavior. Essentially, X became the place you went to act like a dumpster fire. Because most people within occult niches are highly toxic, I tend to not only block them but also block anyone they follow for reasons I’m about to explain.
I really only use that account to criticize occulture, post nudes, or share YouTube videos. Since I’m aware of fed posting, I avoid commenting on political topics or anarchist discourse on the Clearnet. Keep that in mind. If you scroll through my profile, you’ll see me poking fun at chaotes, posting nudes, gushing about or complaining about my husband, sharing dating horror story YouTube videos, or pet grooming videos. If you look at my likes, you’ll only see gay porn, mathematics papers, engineering papers, etc. There’s no mention of anything political, especially genocides.
There was a person I’d never interacted with who was part of a starter pack for occultists. I blocked them. Then I woke up this morning to find I was added to this list:
Chomsky Honks
Genocide apologist posting cringe from a Starbucks as it burns down around themSo, with all that in mind, these occultists I’ve never interacted with added me to a list. I am neither invested in Bluesky nor strongly connected to their network, primarily because I block almost everyone on it and don’t ever look at any feeds whatsoever, including the Home, followers, or Discover feeds. Therefore, the posts I do interact with are from pockets of people way outside my network. It’s kind of like driving to the bathhouse in Atlanta from a small town in Bubbafuck, Georgia, because everyone in your small town is garbage. Same idea, ontologically.
Honestly, I don’t care, because I’ve mostly moved back to Mastodon and blog more.
What they’ve done is implicitly a form of defamation, because they feel slighted and justified in defaming someone they don’t know, simply because a stranger they’ve never spoken to blocked them. I tend to do a basic block on anyone who blocks me, because if you’ve decided you don’t want to see me, there’s probably no good-faith reason for us to engage in the future. It’s likely there’s some malicious intent later on. As you can see with this, I was correct.
So, in order for them to know I blocked them, they had to continuously check who had blocked them, and they believe people who block them should be punished through bullying. Since the description of the list doesn’t fit me, they retaliated out of malice. The idea behind these cliques is pretty simple: they feel threatened by anyone who rejects their normative statements because it means they are being rejected, and they view any form of dissent as an existential threat. As a result, they believe people who reject them, set boundaries, or dissent from the consensus of their culture need to be punished, and the AT protocol provides convenient tools for brigading. Ironically, these people are anti-fascist yet have a very Christian-like evangelical way of viewing the world. The lack of insight is pretty funny.
I’m the child of cult leaders and members with Cluster B personalities, so I’m not clutching my pearls, especially since I’m already set up elsewhere outside of Bluesky. They do not have the means to impose significant consequences on me, so I find it amusing. I genuinely find it funny how they eat each other. I’m not calling anyone to action—I’m just enjoying the fire.
This person wasn’t aware of who I was. We never interacted, and being added to a list that defames me happened directly after I blocked them without any prior interaction. I saw their account from the firehose and wasn’t algorithmically presented with it, meaning we’re not even in the same clique. Now, if they had said something like “spams hashtags, trolls, makes alts,” that would make sense.
When you look at it for what it is, they wanted to defame, disparage, and brigade—punitive actions because they interpreted a boundary as hostile. This is projection, as they are weaponizing a mechanism to enforce boundaries. Do I care? No. I’m just pointing out how it turned its predecessor, X, into what it is now. It became a place for people to harass others, not a space for genuine, good-faith discussions, connections, or even debates. That is not my interpretation.
Well, to anyone who knows, you might ask: Did they block you because you have a particular reputation? No. I am a Web 1.0 mage, so the networks I’m known in have roots and associations in the old forums. The occulture people who have fixated on me for years go all the way back to Wizard Forums, the psionics forums, the unsolved mystery forums, etc., from the early 2000s. If you’re a circa 2016 social media influencer mage, you probably wouldn’t know me—primarily because the moment I see you, I’ll block you. There’s also a moderation block list just for me and my alts.
This behavior is typical of the culture on Bluesky, so much so that it’s a common complaint people now have—many no longer view block lists as legitimate moderation tools. People are being advised to be skeptical of lists with a large number of people.
Oh, I’m not playing the victim here. I don’t care, because I could easily get back at them. I’m infamously vindictive and petty. More importantly, it supports my point and vindicates me. I’m not signaling victimhood; rather, I’m pointing out a culture, albeit one I participate in. Tying this back to my initial point: part of what signaled the death of Twitter as a serious forum and its transformation into X was the bullying. A while ago, I did a phylogenetic memetic analysis that basically showed how the culture on Bluesky is highly derivative of image boards. But don’t you bully and troll people? Yes, yes, I do – on Bluesky, and the lack of moderation and culture enable it. That’s my point.
Bluesky is an accelerationist and reactionary platform that gives you the tools to surveil and harass people. The developers of Bluesky and the AT Protocol have explicitly said they are technological accelerationists and libertarians. I’m not virtue signaling here; rather, I am saying Bluesky is a reactionary platform, so its culture should be understood as performative, hostile, and adversarial—not cooperative or collaborative. Just like Twitter. You can’t do what I do on Bluesky on the fediverse, because the culture won’t allow it.
You saw this type of behavior on Tumblr, where the population carrying the memetics of that culture migrated to Twitter and now Bluesky. Essentially, Bluesky became a place where malice, bullying, and hostile behavior became so normalized that I’m not even upset about lists being weaponized like this. For example, I’m not posting this on Bluesky, and I, myself, have bullied people on Bluesky. But I behave myself on Mastodon. I am using myself as an example. The trolling is happening on Bluesky. The thoughtful posts are happening on Mastodon. The blog this will be posted on is federated, so this is being posted to the fediverse.
That’s what happened to Twitter. It started normalizing hostile, toxic behavior, so that people left the platform and only returned to Twitter for schadenfreude. I have my own WordPress fediverse instance. I am just on Bluesky for the schadenfreude.
-
Bluesky is An Ontological Space for Sadomasochism, Trolling, & Schadenfreude
So, during the initial exodus from Twitter after it became X following Elon Musk’s purchase, many people left but kept their accounts, purposefully to bully, surveil, antagonize, and troll others. People—including me—moved to Bluesky, Mastodon, or both, and used their Twitter accounts purely for harassment and similar behavior. Essentially, X became the place you went to act like a dumpster fire. Because most people within occult niches are highly toxic, I tend to not only block them but also block anyone they follow for reasons I’m about to explain.
I really only use that account to criticize occulture, post nudes, or share YouTube videos. Since I’m aware of fed posting, I avoid commenting on political topics or anarchist discourse on the Clearnet. Keep that in mind. If you scroll through my profile, you’ll see me poking fun at chaotes, posting nudes, gushing about or complaining about my husband, sharing dating horror story YouTube videos, or pet grooming videos. If you look at my likes, you’ll only see gay porn, mathematics papers, engineering papers, etc. There’s no mention of anything political, especially genocides.
There was a person I’d never interacted with who was part of a starter pack for occultists. I blocked them. Then I woke up this morning to find I was added to this list:
Chomsky Honks
Genocide apologist posting cringe from a Starbucks as it burns down around themSo, with all that in mind, these occultists I’ve never interacted with added me to a list. I am neither invested in Bluesky nor strongly connected to their network, primarily because I block almost everyone on it and don’t ever look at any feeds whatsoever, including the Home, followers, or Discover feeds. Therefore, the posts I do interact with are from pockets of people way outside my network. It’s kind of like driving to the bathhouse in Atlanta from a small town in Bubbafuck, Georgia, because everyone in your small town is garbage. Same idea, ontologically.
Honestly, I don’t care, because I’ve mostly moved back to Mastodon and blog more.
What they’ve done is implicitly a form of defamation, because they feel slighted and justified in defaming someone they don’t know, simply because a stranger they’ve never spoken to blocked them. I tend to do a basic block on anyone who blocks me, because if you’ve decided you don’t want to see me, there’s probably no good-faith reason for us to engage in the future. It’s likely there’s some malicious intent later on. As you can see with this, I was correct.
So, in order for them to know I blocked them, they had to continuously check who had blocked them, and they believe people who block them should be punished through bullying. Since the description of the list doesn’t fit me, they retaliated out of malice. The idea behind these cliques is pretty simple: they feel threatened by anyone who rejects their normative statements because it means they are being rejected, and they view any form of dissent as an existential threat. As a result, they believe people who reject them, set boundaries, or dissent from the consensus of their culture need to be punished, and the AT protocol provides convenient tools for brigading. Ironically, these people are anti-fascist yet have a very Christian-like evangelical way of viewing the world. The lack of insight is pretty funny.
I’m the child of cult leaders and members with Cluster B personalities, so I’m not clutching my pearls, especially since I’m already set up elsewhere outside of Bluesky. They do not have the means to impose significant consequences on me, so I find it amusing. I genuinely find it funny how they eat each other. I’m not calling anyone to action—I’m just enjoying the fire.
This person wasn’t aware of who I was. We never interacted, and being added to a list that defames me happened directly after I blocked them without any prior interaction. I saw their account from the firehose and wasn’t algorithmically presented with it, meaning we’re not even in the same clique. Now, if they had said something like “spams hashtags, trolls, makes alts,” that would make sense.
When you look at it for what it is, they wanted to defame, disparage, and brigade—punitive actions because they interpreted a boundary as hostile. This is projection, as they are weaponizing a mechanism to enforce boundaries. Do I care? No. I’m just pointing out how it turned its predecessor, X, into what it is now. It became a place for people to harass others, not a space for genuine, good-faith discussions, connections, or even debates. That is not my interpretation.
Well, to anyone who knows, you might ask: Did they block you because you have a particular reputation? No. I am a Web 1.0 mage, so the networks I’m known in have roots and associations in the old forums. The occulture people who have fixated on me for years go all the way back to Wizard Forums, the psionics forums, the unsolved mystery forums, etc., from the early 2000s. If you’re a circa 2016 social media influencer mage, you probably wouldn’t know me—primarily because the moment I see you, I’ll block you. There’s also a moderation block list just for me and my alts.
This behavior is typical of the culture on Bluesky, so much so that it’s a common complaint people now have—many no longer view block lists as legitimate moderation tools. People are being advised to be skeptical of lists with a large number of people.
Oh, I’m not playing the victim here. I don’t care, because I could easily get back at them. I’m infamously vindictive and petty. More importantly, it supports my point and vindicates me. I’m not signaling victimhood; rather, I’m pointing out a culture, albeit one I participate in. Tying this back to my initial point: part of what signaled the death of Twitter as a serious forum and its transformation into X was the bullying. A while ago, I did a phylogenetic memetic analysis that basically showed how the culture on Bluesky is highly derivative of image boards. But don’t you bully and troll people? Yes, yes, I do – on Bluesky, and the lack of moderation and culture enable it. That’s my point.
Bluesky is an accelerationist and reactionary platform that gives you the tools to surveil and harass people. The developers of Bluesky and the AT Protocol have explicitly said they are technological accelerationists and libertarians. I’m not virtue signaling here; rather, I am saying Bluesky is a reactionary platform, so its culture should be understood as performative, hostile, and adversarial—not cooperative or collaborative. Just like Twitter. You can’t do what I do on Bluesky on the fediverse, because the culture won’t allow it.
You saw this type of behavior on Tumblr, where the population carrying the memetics of that culture migrated to Twitter and now Bluesky. Essentially, Bluesky became a place where malice, bullying, and hostile behavior became so normalized that I’m not even upset about lists being weaponized like this. For example, I’m not posting this on Bluesky, and I, myself, have bullied people on Bluesky. But I behave myself on Mastodon. I am using myself as an example. The trolling is happening on Bluesky. The thoughtful posts are happening on Mastodon. The blog this will be posted on is federated, so this is being posted to the fediverse.
That’s what happened to Twitter. It started normalizing hostile, toxic behavior, so that people left the platform and only returned to Twitter for schadenfreude. I have my own WordPress fediverse instance. I am just on Bluesky for the schadenfreude.
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“How the British Intelligence Network of Astroturfed Muslim Civil Society Groups Is Kept Secret and Deniable”
by David Miller in Tracking Power Update on Substack
@uk_politics @BBC5Live
@BBCRadio4
@BBCNews
@guardian @Independent @thetimes @UKLabour“The Research, Information and Communications Unit and Covert Propaganda”
https://open.substack.com/pub/trackingpower/p/how-the-british-intelligence-network
#Press #UK Intelligence #Network #Astroturf #Muslim #CivilSociety #Covert #Propaganda #RICU #Deniability #HomeOffice #Pottinger #MintPress #Leak
-
“How the British Intelligence Network of Astroturfed Muslim Civil Society Groups Is Kept Secret and Deniable”
by David Miller in Tracking Power Update on Substack
@uk_politics @BBC5Live
@BBCRadio4
@BBCNews
@guardian @Independent @thetimes @UKLabour“The Research, Information and Communications Unit and Covert Propaganda”
https://open.substack.com/pub/trackingpower/p/how-the-british-intelligence-network
#Press #UK Intelligence #Network #Astroturf #Muslim #CivilSociety #Covert #Propaganda #RICU #Deniability #HomeOffice #Pottinger #MintPress #Leak
-
“How the British Intelligence Network of Astroturfed Muslim Civil Society Groups Is Kept Secret and Deniable”
by David Miller in Tracking Power Update on Substack
@uk_politics @BBC5Live
@BBCRadio4
@BBCNews
@guardian @Independent @thetimes @UKLabour“The Research, Information and Communications Unit and Covert Propaganda”
https://open.substack.com/pub/trackingpower/p/how-the-british-intelligence-network
#Press #UK Intelligence #Network #Astroturf #Muslim #CivilSociety #Covert #Propaganda #RICU #Deniability #HomeOffice #Pottinger #MintPress #Leak
-
“How the British Intelligence Network of Astroturfed Muslim Civil Society Groups Is Kept Secret and Deniable”
by David Miller in Tracking Power Update on Substack
@uk_politics @BBC5Live
@BBCRadio4
@BBCNews
@guardian @Independent @thetimes @UKLabour“The Research, Information and Communications Unit and Covert Propaganda”
https://open.substack.com/pub/trackingpower/p/how-the-british-intelligence-network
#Press #UK Intelligence #Network #Astroturf #Muslim #CivilSociety #Covert #Propaganda #RICU #Deniability #HomeOffice #Pottinger #MintPress #Leak
-
🍃 Fake grass is greener but is it worse for the environment?
https://phys.org/news/2025-08-fake-grass-greener-worse-environment.html
#lawns #grass #fakegrass #turf #astroturf #environment #horticulture #plastics