#cynicism — Public Fediverse posts

DATE: August 22, 2026 at 09:00AM
SOURCE: PSYPOST.ORG

** Research quality varies widely from fantastic to small exploratory studies. Please check research methods when conclusions are very important to you. **
-------------------------------------------------

TITLE: People who favor dark humor tend to exhibit more problematic personality traits

URL: https://www.psypost.org/people-who-favor-dark-humor-tend-to-exhibit-more-problematic-personality-traits/

The way a person jokes may offer a subtle glimpse into their underlying psychological makeup and how they handle interpersonal relationships. A recent study published in the Psychology of Aesthetics, Creativity, and the Arts suggests that people who favor darker forms of humor, such as sarcasm and cynicism, tend to show higher levels of maladaptive personality traits. In contrast, those who use lighter, more playful humor tend to display fewer traits associated with personality disorders.

Humor is a universal human behavior that does more than just make people laugh. It serves as a tool for emotional regulation, social bonding, and communicating complex ideas. “Humor is one of the most fascinating forms of human communication, and I have been studying its psychological functions for about 15 years,” said lead author Alberto Dionigi, a psychologist and cognitive behavioral psychotherapist at the Noesis Clinical Center in Italy.

“I am a psychologist and Cognitive Behavioral Psychotherapist, and my main research interest is understanding how humor can influence the way we cope with emotions, relate to other people, and express our personality,” Dionigi explained. Psychologists often break humor down into different comic styles. Lighter styles include fun, benevolent humor, nonsense, and wit, which generally promote positive feelings and social connection.

Darker comic styles include irony, satire, sarcasm, and cynicism. These styles often rely on criticism, mockery, or a sense of superiority, which can strain relationships if used excessively. “We often think of humor as something inherently positive, but this is not always the case,” Dionigi said. “Humor can promote wellbeing, reduce stress, and facilitate social relationships, but it can also be used to criticize, distance ourselves from others, express hostility, or protect ourselves from vulnerability.”

Past research linking humor to personality mostly focused on standard traits, like extraversion or agreeableness. The authors of this new research wanted to explore how these eight specific comic styles align with a wider range of personality disorder traits.

“For this reason, we decided to investigate whether different ways of using humor are associated with specific maladaptive personality traits,” Dionigi added. “Rather than simply asking whether someone has a “good sense of humor,” we examined eight different comic styles, ranging from lighter forms such as fun, benevolent humor, nonsense, and wit to darker forms such as irony, satire, sarcasm, and cynicism.”

The scientists focused on a normative adult sample. This means they studied everyday people rather than patients formally diagnosed with a psychiatric condition. Mental health professionals recognize that personality disorder traits exist on a continuous spectrum. Many people possess subclinical levels of these traits, meaning they have certain cognitive or behavioral tendencies that do not meet the threshold for a full medical diagnosis.

The researchers surveyed 599 Italian adults with an average age of 40. Participants completed the survey online, answering questions from the Comic Style Markers questionnaire. This tool measures how frequently a person uses the eight different humor styles. The survey asked participants to rate statements on a scale from one to seven based on how well the descriptions matched their behavior.

For example, a statement measuring fun was “I am a funny joker,” while a statement measuring sarcasm was “Biting mockery suits me.” Next, the participants completed the Personality Belief Questionnaire-Short Form. This tool measures dysfunctional thinking patterns associated with ten different personality disorder traits. These traits include avoidant, dependent, passive-aggressive, obsessive-compulsive, antisocial, narcissistic, histrionic, schizoid, paranoid, and borderline tendencies.

An avoidant trait was measured with statements like “I should avoid unpleasant situations at all costs.” An antisocial trait was measured with statements such as “Force or cunning is the best way to get things done.” The researchers analyzed the collected data to see which personality traits predicted which humor styles. The authors controlled for the age and sex of the participants during their statistical analysis to isolate the effects of personality.

The findings indicate that darker comic styles are consistently linked to more problematic personality features. “I think the main message is that humor is not simply positive or negative: how we use humor matters,” Dionigi explained. “In our study of 599 Italian adults, we found that darker comic styles, particularly sarcasm and cynicism, were more strongly associated with maladaptive personality traits.”

Sarcasm and cynicism showed the strongest positive associations with passive-aggressive, antisocial, narcissistic, histrionic, and borderline traits. The statistical models explained up to 23 percent of the variance in the use of cynical humor. This indicates a moderate statistical relationship, meaning that almost a quarter of the differences in how often people use cynical humor can be predicted by these specific personality traits.

These patterns suggest that individuals with antagonistic or impulsive tendencies might use sarcasm and cynicism as socially acceptable ways to express dominance. “For example, they were related to traits involving interpersonal antagonism, distrust, hostility, and emotional dysregulation,” Dionigi said. “This does not mean, of course, that a sarcastic person has a personality disorder. Our participants came from the general population, and we investigated personality traits on a continuum, not clinical diagnoses.”

Irony and satire also showed positive links to maladaptive traits, though the associations were slightly weaker. Satire, which involves mocking foolish behavior to correct it, was associated with both narcissistic and obsessive-compulsive traits. The researchers propose that narcissistic individuals might use satire to mask their feelings of superiority in a socially acceptable format.

Meanwhile, those with obsessive-compulsive traits might use satirical humor as a way to enforce moral rules and maintain a sense of order. Irony was positively linked to borderline, paranoid, and obsessive-compulsive patterns. The authors suspect irony provides a cognitive distance that helps people regulate intense emotions. “Similarly, irony may sometimes help people create emotional distance from difficult experiences,” Dionigi noted.

The researchers caution against labeling any humor style as strictly good or bad. “One aspect I would emphasize is that our results should not be interpreted as saying that some forms of humor are “healthy” and others are “pathological.” Humor is much more complex than that,” Dionigi explained. “Even darker styles can have adaptive functions depending on the context. Satire, for example, can be used to criticize problematic behaviors or social norms and encourage reflection and change.”

Lighter comic styles were mostly isolated from these darker personality traits. “On the other hand, lighter forms of humor were generally less strongly related to maladaptive personality traits and were more connected with social affiliation, playfulness, and cognitive flexibility,” Dionigi added. Fun and benevolent humor showed weak or negative associations with maladaptive tendencies.

Avoidant personality traits, which involve a deep fear of social rejection, were negatively associated with fun, benevolent humor, nonsense, and wit. People with high avoidant traits tend to withdraw from social situations, which likely reduces their opportunities to engage in playful banter and share jokes.

“A frequent reliance on cynical or sarcastic humor, for example, may sometimes offer clues about hostility, distrust, or the need to maintain emotional distance, while difficulty using more affiliative forms of humor may be associated with social withdrawal or vulnerability,” Dionigi said.

The histrionic personality trait, characterized by excessive attention-seeking and emotionality, heavily predicted the use of fun and humor. Individuals with these traits may use playful jokes to maintain the spotlight and engage with their audience. Wit, which involves clever verbal associations, was positively associated with narcissism, suggesting that self-enhancing individuals might use intellectual humor to impress others. Additionally, men in the sample reported higher scores on the darker, more maladaptive forms of humor than women did.

“So, perhaps the most interesting takeaway is that our sense of humor may tell us something about the way we relate to ourselves and to other people,” Dionigi said. “Humor can be a way of connecting, playing, and sharing positive emotions, but it can also become a socially acceptable way of expressing hostility, keeping emotional distance, or defending ourselves.”

A cross-sectional design was used for this research, meaning all data was collected at a single point in time. This setup indicates associations between variables but cannot determine cause and effect. “An important caveat is that this was a cross-sectional study, so we cannot establish causality,” Dionigi explained. “We can say that certain personality traits and comic styles are associated, but we cannot say that personality traits cause a particular type of humor, or vice versa.”

The study relied entirely on self-reported questionnaires. People often lack objective self-awareness, especially regarding their own negative traits, and they may answer in ways that make them look better than they actually are.

“Humor is a highly interpersonal behavior, so future studies could include ratings from partners, friends, or clinicians, as well as behavioral measures of how people actually use humor in real-life interactions,” Dionigi noted.

The sample consisted primarily of Italian adults, and nearly 73 percent of the participants were women. This demographic imbalance and specific cultural setting might limit how well the findings apply to other populations. “Our sample was also composed mainly of nonclinical Italian adults, so the findings should not automatically be generalized to people diagnosed with personality disorders or to other cultures,” Dionigi said.

Future studies could track people over time and across different cultures to better understand how humor and personality interact throughout a lifespan.

“One question I find particularly interesting for future research is whether it is not only which humor style people use, but also how effectively they use it that matters,” Dionigi explained. “Two people may both use sarcasm, for example, but with very different interpersonal effects. It would also be interesting to study these relationships in clinical populations and among professional humor performers.”

As a psychotherapist, Dionigi hopes this research encourages people to think more deeply about their own habits. “So, rather than asking “Is humor good or bad?”, perhaps we should ask: “What kind of humor am I using, with whom, and what function is it serving in this particular moment?””

The study, “Humor and Personality Disorders: Associations Between Comic Styles and Maladaptive Personality Traits in a Normative Adult Sample,” was authored by Alberto Dionigi, Mirko Duradoni, and Laura Vagnoli.

URL: https://www.psypost.org/people-who-favor-dark-humor-tend-to-exhibit-more-problematic-personality-traits/

-------------------------------------------------

Private, vetted email list for mental health professionals: https://www.clinicians-exchange.org

Unofficial Psychology Today Xitter to toot feed at Psych Today Unofficial Bot @PTUnofficialBot

-------------------------------------------------

#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #DarkHumor #HumorAndMentalHealth #ComicStyles #PersonalityTraits #Sarcasm #Cynicism #Satire #HumorResearch #PsychologyOfHumor #SocialBehavior

I saw this on Mastodon and almost had a stroke.

@davidgerard wrote:

“Most of the AI coding claims are conveniently nondisprovable. What studies there are show it not helping coding at all, or making it worse

But SO MANY LOUD ANECDOTES! Trust me my friend, I am the most efficient coder in the land now. No, you can’t see it. No, I didn’t measure. But if you don’t believe me, you are clearly a fool.

These guys had one good experience with the bot, they got one-shotted, and now if you say “perhaps the bot is not all that” they act like you’re trying to take their cocaine away.”

First, the term is falsifiable, and proving propositions about algorithms (i.e., code) is part of what I do for a living. Mathematically human-written code and AI-written code can be tested, which means you can falsify propositions about them. You would test them the same way.

There is no intrinsic mathematical distinction between code written by a person and code produced by an AI system. In both cases, the result is a formal program made of logic and structure. In principle, the same testing techniques can be applied to each. If it were really nondisprovable, you could not test to see what is generated by a human and what is generated by AI. But you can test it. Studies have found that AI-generated code tends to exhibit a higher frequency of certain types of defects. So, reviewers and testers know what logic flaws and security weaknesses to look for. This would not be the case if it were nondisprovable.

You can study this from datasets where the source of the code is known. You can use open-source pull requests identified as AI-assisted versus those written without such tools. You then evaluate both groups using the same industry-standard analysis tools: static analyzers, complexity metrics, security scanners, and defect classification systems. These tools flag bugs, vulnerabilities, performance issues, and maintainability concerns. They do so in a consistent way across samples.

A widely cited analysis of 470 real pull requests reported that AI-generated contributions contained roughly 1.7 times as many issues on average as human-written ones. The difference included a higher number of critical and major defects. It also included more logic and security-related problems. Because these findings rely on standard measurement tools — counting defects, grading severity, and comparing issue rates — the results are grounded in observable data. Again, I am making a point here. It’s testable and therefore disproveable.

This is a good paper that goes into it:

In this paper, we present a large-scale comparison of code authored by human developers and three state-of-the-art LLMs, i.e., ChatGPT, DeepSeek-Coder, and Qwen-Coder, on multiple dimensions of software quality: code defects, security vulnerabilities, and structural complexity. Our evaluation spans over 500k code samples in two widely used languages, Python and Java, classifying defects via Orthogonal Defect Classification and security vulnerabilities using the Common Weakness Enumeration. We find that AI-generated code is generally simpler and more repetitive, yet more prone to unused constructs and hardcoded debugging, while human-written code exhibits greater structural complexity and a higher concentration of maintainability issues. Notably, AI-generated code also contains more high-risk security vulnerabilities. These findings highlight the distinct defect profiles of AI- and human-authored code and underscore the need for specialized quality assurance practices in AI-assisted programming.

https://arxiv.org/abs/2508.21634

Something I’ve started to notice about a lot of the content on social media platforms is that most of the posts people are liking, sharing, and memetically mutating—and then spreading virally—usually don’t include any citations, sources, or receipts. It’s often just some out-of-context screenshot with no reference link or actual sources.

A lot of the anti-AI content is not genuine critique. It’s often misinformation, but people who hate AI don’t question it or ask for sources because it aligns with their biases. The propaganda on social media has gotten so bad that anything other than heavily curated and vetted feeds is pretty much useless, and it’s filled with all sorts of memetic contagions with nasty hooks that are optimized for you algorithmically. I am at the point where I will disregard anything that is not followed up with a source. Period. It is all optimized to persuade, coerce, or piss you off. I am only writing about this because this I’m actually able to contribute genuine information about the topic.

That they said symbolic propositions written by AI agents (i.e., code) are non-disprovable because they were written by AI boggles my mind. It’s like saying that an article written in English by AI is not English because AI generated it. It might be a bad piece of text, but it’s syntactically, semantically, and grammatically English.

Basically, any string of data can be represented in a base-2 system, where it can be interpreted as bits (0s and 1s). Those bits can be used as the basis for symbolic reasoning. In formal propositional logic, a proposition is a sequence of symbols constructed according to strict syntax rules (atomic variables plus logical connectives). Under a given semantics, it is assigned exactly one truth value (true or false) in a two-valued logic system.

They are essentially saying that code written by AI is not binary, isn’t symbolically logical at all, and cannot be evaluated as true or false by implying it is nondisproveable. At the lowest level, compiled code consists of binary machine instructions that a processor executes. At higher levels, source code is written in symbolic syntax that humans and tools use to express logic and structure. You can also translate parts of code into formal logic expressions. For example, conditions and assertions in a program can be modeled as Boolean formulas. Tools like SAT/SMT solvers or symbolic execution engines check those formulas for satisfiability or correctness. It blows my mind how confidently people talk about things they do not understand.

Furthermore that they don’t realize the projection is wild to me.

@davidgerard wrote:

“But SO MANY LOUD ANECDOTES! Trust me my friend, I am the most efficient coder in the land now. No, you can’t see it. No, I didn’t measure. But if you don’t believe me, you are clearly a fool.”

They are presenting a story—i.e., saying that the studies are not disprovable—and accusing computer scientists of using anecdotal evidence without actually providing evidence to support this, while expecting people to take it prima facie. You’re doing what you are accusing others of doing.

It comes down to this: they feel that people ought not to use AI, so they are tacitly committed to a future in which people do not use AI. For example, a major argument against AI is the damage it is doing to resources, which is driving up the prices of computer components, as well as the ecological harm it causes. They feel justified in lying and misinforming others if it achieves the outcome they want—people not using AI because it is bad for the environment. That is a very strong point, but most people don’t care about that, which is why they lie about things people would care about.

It’s corrupt. And what’s really scary is that people don’t recognize when they are part of corruption or a corrupt conspiracy to misinform. Well, they recognize it when they see the other side doing it, that is. No one is more dangerous than people who feel righteous in what they are doing.

@cloudskater wrote:

Some instances are run by bad people. Hell, a few projects like Lemmy and Matrix are DEVELOPED by assholes, but the FLOSS and federated nature of these platforms allows us to bypass/fork them and create healthy spaces outside their reach.

Nope, that is actually what is killing the fediverse. I just explained here:

The issue is the divergence in semantic interpretation that emerges at the interpretation layer. ActivityPub standardizes message delivery and defines common activity types. However, it leaves extension semantics and application-layer policy decisions to individual implementations. Servers may introduce custom JSON-LD namespaces and enforce local behaviors, such as reply restrictions, while remaining protocol-compliant. But, the noise created by divergences are problematic, because it creates unexpected, unintended, and unpredictable behavior.

Divergence appears when implementations rely on non-normative metadata and assume reciprocal handling to preserve a consistent user experience. Behavioral alignment then varies. Syntactic exchange succeeds, but behavioral consistency is not guaranteed. Though instances continue to federate at the transport level, policy semantics and processing logic differ across deployments. Those differences produce inconsistent experiences and results between implementations.

That leads to fragmentation, specifically semantic or behavioral fragmentation and an inconsistent user experiences. ActivityPub ensures syntactic interoperability, but semantic interoperability (everyone interprets and enforces rules the same way) varies. This creates a system that is federated at the transport level yet fragmented in behavior and expectations across implementations. It is funny how the thing that the fediverse touted has made the entire thing very brittle. ActivityPub technically federates correctly, but semantically falls apart once servers start adding their own behavioral rules.

https://neon-blue-demon-wyrm.x10.network/archives/16932

FYI, I’m not doing culture wars or political debates. I’m just saying this idea of “forking away” from them is literally breaking the fediverse’s distributed network and creating all kinds of issues with semantic interoperability. Yes, federation is still happening at the delivery level, but the semantic issues are out of fucking control. You are a federation by the very sheer skin of your teeth.

The reason why developers are leaving the fediverse is because you folks don’t take criticism. You respond to criticism with — I’m being so serious right now — political manifestos and harassing developers. ActivityPub developers and authors oversold you folks on the capabilities of ActivityStreams. They flat-out lied to y’all.

↬bark.lgbt/@cloudskater/116080965694723006

ActivityPub Server’s Custom Reply‑Control Extensions Undermine Federation

It seems like Activitbypub developers are extending ActivityPub with optional metadata to fix a lot of its issues, but that is still problematic. Trying to add moderation tools and user control to threads seems to be the ongoing battle. I am fascinated by dumpster fires, so I’ve started looking at the ActivityPub protocol in detail. I tend to become fascinated with things that are going down in flames.

As a brief recap of the problem:

So, one of the very popular features on Bluesky—also popular on Twitter—is the ability to select who can reply to a post. A major issue in the Fediverse is the inability to decide who can reply, and once you block someone, their harassing reply is still there. I honestly thought it was simply a case of them choosing not to add or address it for cultural reasons. What is clear from that thread is that they were always aware that the ActivityPub protocol and most Fediverse implementations don’t provide a universal way to control reply visibility or enforce blocks across instances.

An ActivityPub server that has reply control is GoToSocial. ActivityPub, as defined by the W3C specification, standardizes how servers federate activities. It defines actors, inboxes, outboxes, and activity types (Create, Follow, Like, Announce, etc.) expressed using ActivityStreams 2.0. It also specifies delivery mechanics (including how a Create activity reaches another server’s inbox) and how collections behave.

The specification does not include interaction policy semantics such as “only followers may reply” or “replies require manual approval.” There is no field in the normative vocabulary requiring conforming servers to enforce reply permissions. That category of rule is outside the protocol’s defined contract.

GoToSocial implements reply controls through what it calls interaction policies. These appear as additional properties on ActivityStreams objects using a custom JSON-LD namespace controlled by the GoToSocial project.

JSON-LD permits additional namespaced terms. This means the document remains structurally valid ActivityStreams and federates normally. The meaning of those custom fields, however, comes from GoToSocial’s own documentation and implementation. Other servers can ignore them without violating ActivityPub because they are not part of the interoperable core vocabulary.

Enforcement occurs locally. When a remote server sends a reply—a Create activity whose object references another via inReplyTo—ActivityPub governs delivery, not acceptance criteria. Whether the receiving server checks a reply policy, rejects the activity, queues it, or displays it is determined in the server’s inbox-processing code. The decision to accept, display, or require approval happens after successful protocol-level delivery. This behavior belongs to the application layer.

These are server-side features layered on top of ActivityPub’s transport and data model that are not actually part of ActivityPub. The protocol ensures standardized delivery of activities; however, the server implementation defines additional constraints and user-facing behavior. Two GoToSocial instances may both recognize and act on the same extension fields. However, a different implementation, such as Mastodon, has no obligation under the specification to interpret or enforce GoToSocial’s interactionPolicy properties. These fields function as extension metadata rather than protocol requirements.

The semantics of GoToSocial are not part of the specification’s defined vocabulary and processing rules for ActivityPub. They no longer operate purely at the protocol layer; it has become an application-layer contract implemented by specific servers.

Let’s use the AT Protocol as an example. Bluesky’s direct messages (DMs) are not currently part of the AT Protocol (ATProto). The AT Protocol has nothing that specifies anything for DMs, so DMs are not part of the AT Protocol. The AT Protocol was designed to handle public social interactions, but it does not define private or encrypted messaging. Bluesky implemented DMs at the application level, outside of the core protocol. DMs are centralized and stored on Bluesky’s servers. What is happening with servers like GoToSocial is sort of like that. The difference is that the AT Protocol was designed for different app views; ActivityPub was not.

The issue is the divergence in semantic interpretation that emerges at the interpretation layer. ActivityPub standardizes message delivery and defines common activity types. However, it leaves extension semantics and application-layer policy decisions to individual implementations. Servers may introduce custom JSON-LD namespaces and enforce local behaviors, such as reply restrictions, while remaining protocol-compliant. But, the noise created by divergences are problematic, because it creates unexpected, unintended, and unpredictable behavior.

Divergence appears when implementations rely on non-normative metadata and assume reciprocal handling to preserve a consistent user experience. Behavioral alignment then varies. Syntactic exchange succeeds, but behavioral consistency is not guaranteed. Though instances continue to federate at the transport level, policy semantics and processing logic differ across deployments. Those differences produce inconsistent experiences and results between implementations.

That leads to fragmentation, specifically semantic or behavioral fragmentation and an inconsistent user experiences. ActivityPub ensures syntactic interoperability, but semantic interoperability (everyone interprets and enforces rules the same way) varies. This creates a system that is federated at the transport level yet fragmented in behavior and expectations across implementations. It is funny how the thing that the fediverse touted has made the entire thing very brittle. ActivityPub technically federates correctly, but semantically falls apart once servers start adding their own behavioral rules.

Stepping Back From Social Media To Read a Book

I’m taking a break. After spending like two years in the worst parts of the Internet modeling the memetic spread of conspiracy-driven behavioral patterns and developing social media software as a side hustle, I think I’m going to take a step back and… I don’t know… maybe read a book? lol.

I’m a Computational Biologist who pretty much studies the memetics of conspiracy theories and how they act as another vector/epidemiological layer. I’ve also been working on various contracts for social media development stuff. Working on the shit I’ve been working on for years forces you to see the worst parts of people that they split off. It makes you hate everyone — and I mean everyone.

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

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

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

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

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

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

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

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

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

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

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

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

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

Bluesky mentions that here:

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

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

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

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

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

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

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

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

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

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

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

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

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.

A quotation from Herbert Hoover

Our greatest danger is not from invasion by foreign armies. Our dangers are that we may commit suicide from within by complaisance with evil. Or by public tolerance of scandalous behavior. Or by cynical acceptance of dishonor. These evils have defeated nations many times in human history.

Herbert Hoover (1874-1964) American engineer, bureaucrat, US President (1929-33)
Speech (1951-08-30), “Concerning Honor in Public Life,” Iowa Centennial Celebration, Des Moines, Iowa (radio broadcast)

More info about this quote: wist.info/hoover-herbert/78658…

#quote #quotes #quotation #qotd #herberthoover #complaisance #cynicism #danger #decline #dishonor #evil #scandal #threat #nationalsecurity #nationalstrength

Sunday, April 27 2025

Russia attacked Chornobyl Nuclear Plant in February, damaging confinement. Can it be fully restored? — US signals support for Europe’s peacekeeping coalition in Ukraine — Russia training to integrate motorcycles into summer offensive in Ukraine — Interpol investigates Russian company for human trafficking over African workers in Tatarstan drone factory … and more

https://activitypub.writeworks.uk/2025/04/sunday-april-27-2025/

Here is what will happen on day one of Trump’s presidency, according to Project 2025

With Republicans now holding bare majorities in both chambers of Congress, the gloves come off.

As Trump utters the last phrase of the oath of office
– “so help me God”
– the first phase of what #Project2025’s authors call
“the playbook” begins.

❌First come the firings.
Thousands of federal, non-partisan civil servants
–environmental and food safety regulators;
authorities in disaster relief coordination;
attorneys overseeing anti-discrimination policies in housing, education and employment;
medical and scientific researchers
– receive #immediate #layoff notices.
💥Many will not be replaced, as entire federal programs and agencies are shuttered.

The new personnel that do arrive come from conservative thinktanks, or are 💥rightwing activists who applied through the Project 2025 application database.
🔥Political #cronyism is now the official hiring policy of the US federal government.

❌Next come the #roundups.
As drafted by the Maga nativist-in-chief #Stephen #Miller,
a broad range of law enforcement, from the national guard to state and local police are deputized
for a new #deportation #army.

Sweeps of neighborhoods and businesses take aim at blue states and cities,
but general terror is their intended goal.
#Detention #centers are established on military bases and federal facilities with quick access to airfields to execute #mass #removals.
Nearly a million lawfully present immigrants are stripped of their legal protections, subjecting them to immediate deportation.
🔸An end to Daca and a return of the Muslim ban follow.
In the following months other parts of the agenda unfold.

🆘Cuts in corporate taxes so generous they would make the robber barons blush.

An end to federal funding for public television and radio that forces many local stations to shutter.

The termination of Head Start programs leaves hundreds of thousands of parents and guardians without preschool or childcare.

The elimination of the Department of Education and programs like Title I halt funding and many protections for students with disabilities, English learners and students from low-income households.

Pornography is criminalized.

Ditto for abortion rights, emergency contraception and many reproductive health programs.

Adiós also to most public sector unions, labor organizing rights and anti-poverty programs.

⭐️It can be difficult at times to distinguish the hyperbole of Trump and the Maga movement from actual governing plans.
“Build the wall” was always more of a campaign performance and fundraising stunt than a policy blueprint.

But after attending several rightwing conferences and rallies for research in the last year, I have little reason to doubt their intentions this time around.

🔥I’ve heard Miller at CPAC describethe deportation plans in chilling detail.

I heard speaker after speaker at a Turning Point USA conference promise #violence and #retribution against political opponents,
the dismantling of nearly all public goods,
and plans to bring a shrill #Christian #nationalism to the center of governance and civic life.

❌I’ve listened to unapologetic defenses of #eugenics and scientific #racism on rightwing media channels with millions of followers.

And perhaps most frighteningly, I’ve observed growing numbers of
young people,
people of color and others outside of the traditional conservative base
join the #Maga faithful and embrace the #cynicism and #demonization that is the heartbeat of the contemporary right.

Conservatives often celebrate the unity of their governing philosophy, rooted in small government, entrepreneurship, faith and family.

But there is nothing coherent or rational about these policies.
#Plunder is the prevailing principle.

And these ideas are 👉not limited to the #Heritage #Foundation or Trump alone.
🩸They have been embraced across a network of rightwing formations, some with agendas even more extreme than Project 2025.‼️

https://www.theguardian.com/commentisfree/article/2024/sep/09/trump-presidency-day-one-project-2024?CMP=Share_iOSApp_Other

I've developed such cynicism of social media I didn't use my name for my account here. I did use it back in the naive days of early bird site.

Wow, did I get that the wrong way around?!

Starting to regret the pseudonym now. #anonymously #startagain #freshstart #cynicism