Recursively apply patterns for pathfinding
#HackerNews #Recursively #apply #patterns #for #pathfinding #pathfinding #algorithms #recursive #patterns #coding #techniques #software #development
Aderenti Escapes su mastodon
boosted
The Conversation: Algorithms that customize marketing to your phone could also influence your views on warfare https://theconversation.com/algorithms-that-customize-marketing-to-your-phone-could-also-influence-your-views-on-warfare-274817 @TheConversationUS #algorithms
The Conversation: Algorithms that customize marketing to your phone could also influence your views on warfare https://theconversation.com/algorithms-that-customize-marketing-to-your-phone-could-also-influence-your-views-on-warfare-274817 @TheConversationUS #algorithms
🫧 socialcoding..
boosted
"Feed algorithms are widely suspected to influence political attitudes. However, previous evidence from switching off the algorithm on Meta platforms found no political effects1. Here we present results from a 2023 field experiment on Elon Musk’s platform X shedding light on this puzzle. We assigned active US-based users randomly to either an algorithmic or a chronological feed for 7 weeks, measuring political attitudes and online behaviour. Switching from a chronological to an algorithmic feed increased engagement and shifted political opinion towards more conservative positions, particularly regarding policy priorities, perceptions of criminal investigations into Donald Trump and views on the war in Ukraine. In contrast, switching from the algorithmic to the chronological feed had no comparable effects. Neither switching the algorithm on nor switching it off significantly affected affective polarization or self-reported partisanship. To investigate the mechanism, we analysed users’ feed content and behaviour. We found that the algorithm promotes conservative content and demotes posts by traditional media. Exposure to algorithmic content leads users to follow conservative political activist accounts, which they continue to follow even after switching off the algorithm, helping explain the asymmetry in effects. These results suggest that initial exposure to X’s algorithm has persistent effects on users’ current political attitudes and account-following behaviour, even in the absence of a detectable effect on partisanship."
https://www.nature.com/articles/s41586-026-10098-2
#SocialMedia #Algorithms #Twitter #Politics #RecommendationAlgorithms #PublicOpinion #Propaganda
"Feed algorithms are widely suspected to influence political attitudes. However, previous evidence from switching off the algorithm on Meta platforms found no political effects1. Here we present results from a 2023 field experiment on Elon Musk’s platform X shedding light on this puzzle. We assigned active US-based users randomly to either an algorithmic or a chronological feed for 7 weeks, measuring political attitudes and online behaviour. Switching from a chronological to an algorithmic feed increased engagement and shifted political opinion towards more conservative positions, particularly regarding policy priorities, perceptions of criminal investigations into Donald Trump and views on the war in Ukraine. In contrast, switching from the algorithmic to the chronological feed had no comparable effects. Neither switching the algorithm on nor switching it off significantly affected affective polarization or self-reported partisanship. To investigate the mechanism, we analysed users’ feed content and behaviour. We found that the algorithm promotes conservative content and demotes posts by traditional media. Exposure to algorithmic content leads users to follow conservative political activist accounts, which they continue to follow even after switching off the algorithm, helping explain the asymmetry in effects. These results suggest that initial exposure to X’s algorithm has persistent effects on users’ current political attitudes and account-following behaviour, even in the absence of a detectable effect on partisanship."
https://www.nature.com/articles/s41586-026-10098-2
#SocialMedia #Algorithms #Twitter #Politics #RecommendationAlgorithms #PublicOpinion #Propaganda
@reiver ⊼ (Charles) :batman:
and 1 other
boosted
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.
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.
Chip Butty
and 3 others
boosted
Incredible dedication to indexing in Kleinberg & Tardos.
#Algorithms #Algorithmics #ComputerScience #Books #ProfessorLife #Textbook #AcademicMastodon #AcademicChatter
Incredible dedication to indexing in Kleinberg & Tardos.
#Algorithms #Algorithmics #ComputerScience #Books #ProfessorLife #Textbook #AcademicMastodon #AcademicChatter
When I open specific commercial social media and read certain threads, I wonder if they’re full of bots or idiots.
I hope it’s the former, but I fear it’s the latter…
@stefano It's been my experience for years now that #instagram and #twitter are mostly populated by #bots.
I avoid #meta platforms as much as possible but in the times I have to log in, only bots and #toxic #algorithms are palpable.
#Reddit is marginally better. While there are (valuable) communities populated by real humans, the signal to noise ratio can be quite low. Unfortunately this isn't limited to bots.
Djoerd Hiemstra 🍉
boosted
My student walked into my office and stared at the open copies of Russell & Norvig and Kleinberg & Tardos on my desk, with a look of shock and horror on their face, and then went: Do you have time to read all of that‽
I mean... given the notes scribbled in the margins and the bookmarks sticking out of my books, I can hardly deny that I've read at least parts of them in quite some detail. If I admit that, however, my students are no longer going to buy the "sorry I don't have time for an extra meeting" line...
Anybody have a good comeback for me for the next time this happens? This time I just went with "er... that's kind of the idea of studying... that you read your textbooks..." 🤦♀️
#ProfessorLife #AI #Algorithms #Students #AcademicChatter #AcademicMastodon #ArtificialIntelligence #Studying
My student walked into my office and stared at the open copies of Russell & Norvig and Kleinberg & Tardos on my desk, with a look of shock and horror on their face, and then went: Do you have time to read all of that‽
I mean... given the notes scribbled in the margins and the bookmarks sticking out of my books, I can hardly deny that I've read at least parts of them in quite some detail. If I admit that, however, my students are no longer going to buy the "sorry I don't have time for an extra meeting" line...
Anybody have a good comeback for me for the next time this happens? This time I just went with "er... that's kind of the idea of studying... that you read your textbooks..." 🤦♀️
#ProfessorLife #AI #Algorithms #Students #AcademicChatter #AcademicMastodon #ArtificialIntelligence #Studying
Annoying when Zoom mobile app goes into safe driving mode while I'm out walking the dog. A lot of work has gone into turning phone/watch accelerometer data into activity tracking. Maybe Zoom can adopt some of that? #UI #algorithms
Claudius Link
boosted
"Zieht eure Leserschaft konsequent von US-kontrollierten Plattformen weg. Nicht irgendwann. Nicht »wenn Zeit ist«. Sondern jetzt, solange es noch geht."
Ein Appell von Mike im @kuketzblog , den ich nur unterstreichen kann. Meint zwar in erster Linie #Medien, lässt sich aber durchaus an jeden richten, der sich auf Plattformen wie Facebook, X oder Linkedin rumtreibt.
#unplugbigtech #unplugtrump #bigtech #algorithms #shadowban #fascism #DigitaleSouveränität
https://www.kuketz-blog.de/linkedin-shadow-bans-und-die-abhaengigkeit-von-us-plattformen/
"Zieht eure Leserschaft konsequent von US-kontrollierten Plattformen weg. Nicht irgendwann. Nicht »wenn Zeit ist«. Sondern jetzt, solange es noch geht."
Ein Appell von Mike im @kuketzblog , den ich nur unterstreichen kann. Meint zwar in erster Linie #Medien, lässt sich aber durchaus an jeden richten, der sich auf Plattformen wie Facebook, X oder Linkedin rumtreibt.
#unplugbigtech #unplugtrump #bigtech #algorithms #shadowban #fascism #DigitaleSouveränität
https://www.kuketz-blog.de/linkedin-shadow-bans-und-die-abhaengigkeit-von-us-plattformen/