Lmst

Screenshot as I'm visually validating a (TINY) portion of our model of an irrigation district's water distribution network with a bespoke viewer made with Cytoscape.

If you work with #Graph, #Network, #DAG, or graph structures in general, #Cytoscape is a wonderful library to work with. It has lots of plugins, layouts, and examples.

#Neon #Infrastructure #PhysicalInfrastructure

A graph-based model of irrigation water distribution infrastructure with a cool neon 80's color style.

February 2026 WikiPathways update: 95 edits by 9 contributorsin the last month. More news at https://github.com/wikipathways/wikipathways-help/discussions/221 Accessible via #webservices, #rstats, #pathvisio and #cytoscape. Supported by #awsopen. https://www.wikipathways.org/index.php/Download_Pathways

#bioinformatics #openscience #opensource

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

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

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

Bluesky mentions that here:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

The Virulent Infection of BlueSky by Extremely Online, Brain-Rotten Zombies from X Continues

So, it appears a new migration from Twitter to Bluesky is underway. It appears to be some of the most virulent former 4chan users possible. Yep, I got off Bluesky just in time, lol. I’ve been keeping tabs on a particularly virulent and toxic subgraph on Twitter for years. It pretty much stayed off Bluesky because they couldn’t act like abusive dumpster fires there. Welp, looks like they’re becoming more active on Bluesky. It’s not looking good over there.

That they are on the move says something. It’s sort of like how the US is suddenly a place that is hospitable to measles. It was all but eradicated here.

My husband likes to say that you can tell where not to be by where I am looking from somewhere else. I like fires. So if I am observing your platform or community from a distance, you probably don’t want to be there.

Edit:

I had originally posted the above on a now-defunct federated blog. It got blasted to Mastodon. Someone replied and asked what I think is causing this. I debated actually answering, then decided that I’ve had enough of the dumpster fire that is social media. I decided not to wade through social media tech discourse into what will mostly likely be an Internet argument with a complete stranger. I am a techie dragon, and I engage with things to learn how they work so I can tinker with them. I only engaged with tech discourse to get my hands on how the tech works. There’s nothing in it for me to be part of larger conversations. Arguing with random strangers on social media is not an epistemically useful format. I do think I should answer, though. Just on my blog.

I treat social media like I do an addictive substance. I do not believe in abstinence, but I do believe in harm-reduction paradigms, so when I see everyone overdosing on social media, I pull back and shut down a lot of accounts. The Fediverse instance where the first part of this blog post was posted has been taken down, moved to this blog, and this section appended to it.

I often use the word weeb pejoratively. Here, I am using it categorically. There really isn’t an “official” name outside of otaku or weeb culture. I am at the fringes and intersections of it as a furry. My husband is a millennial weeb. With that being said—

The migration is in large part because Bluesky is capturing the otaku/weeb niche of X. X hosted networks that were ecosystems of “anime fans.” These included anime and manga artists, doujin and hentai artists, VTuber fans, NSFW illustrators, fandom shitposters, niche fetish communities, and other chronically and extremely online content creators and influencers. That culture relied heavily on timelines, informal networks, and discovery through reposts, replies, and algorithmic amplification.

Elon Musk pretty much destabilized X’s ecosystems and social networks from multiple directions at once. Algorithm changes made reach inconsistent. Moderation created anxiety and uncertainty about what would get suppressed or unintentionally “viral”. Bots, engagement farming, and blue-check reply spam actively poisoned fandom conversations.

Bluesky is the memetic and cultural progeny of early imageboard cultures. I conducted a phylogenetic analysis of the memetics, which you can check out here:

Bluesky is a competitor of X for otaku and fandom communities. Bluesky has a lot of the aspects of old Twitter dynamics around which fandom culture evolved. Recently, Bluesky introduced something big in those communities: going live. Since X is no longer habitable for weebs, they are moving to Bluesky.

For example, the AT protocol already has PinkSea:

https://pinksea.art

And, of course, there is WAFRN:

https://app.wafrn.net

I cope and deal with issues via personal, private sublimation and not so much exhibitionism of my art or consumption of art. So, while I do make comic books and do a shit ton of weeby art, it’s for the purpose of sublimation, so I’m not too interested in being a part of a community. That’s a large reason I am not active in those spaces. I’m quite cynical, in general, so I am suspicious of any community — and I mean any community, at all. Honestly, I am mildly contemptuous of mass participation or any sense of belonging. So, my art stays private, because it is created for me – and just me.