A new European ruling on algorithmic amplification determines if an operator controls how content spreads on a platform. But applying it to open social networks turns out to be a problem.
Blacksky Algorithms - Open Collective
Decentralized social media built for community power, culture, and collective freedom.
Social media algorithms can be redesigned to bridge divides — here’s how
"It falls to both the tech companies that built these systems and an engaged public to create technologies designed for social cohesion."
Bluesky & Open Social Media Tech
A New Social
Our mission is to liberate people's networks from their platforms, enabling The Last Network Effect and leveling the playing field across the open social web.
A New Social
Our mission is to liberate people's networks from their platforms, enabling The Last Network Effect and leveling the playing field across the open social web.
AI, Agency and Protocols_ Power and Governance in Open Social Networks.pdf
Introducing GreenEarth
We're building advanced open source algorithms for social media
Modelling Opinion Dynamics in the Age of Algorithmic Personalisation
Modern technology has drastically changed the way we interact and consume information. For example, online social platforms allow for seamless communication exchanges at an unprecedented scale. However, we are still bounded by cognitive and temporal constraints. Our attention is limited and extremely valuable. Algorithmic personalisation has become a standard approach to tackle the information overload problem. As result, the exposure to our friends' opinions and our perception about important issues might be distorted. However, the effects of algorithmic gatekeeping on our hyper-connected society are poorly understood. Here, we devise an opinion dynamics model where individuals are connected through a social network and adopt opinions as function of the view points they are exposed to. We apply various filtering algorithms that select the opinions shown to users i) at random ii) considering time ordering or iii) their current beliefs. Furthermore, we investigate the interplay between such mechanisms and crucial features of real networks. We found that algorithmic filtering might influence opinions' share and distributions, especially in case information is biased towards the current opinion of each user. These effects are reinforced in networks featuring topological and spatial correlations where echo chambers and polarisation emerge. Conversely, heterogeneity in connectivity patterns reduces such tendency. We consider also a scenario where one opinion, through nudging, is centrally pushed to all users. Interestingly, even minimal nudging is able to change the status quo moving it towards the desired view point. Our findings suggest that simple filtering algorithms might be powerful tools to regulate opinion dynamics taking place on social networks
The Algorithm, Apparently Chronological
A German court has explicitly named Mastodon and Bluesky as positive examples of social networks that could retain hosting protection. It gets Bluesky’s feeds wrong, but its reasoning about user control might be more useful than it realises.
Our Social Media is Broken. Is Decentralization the Fix? | Internet Archive Blogs
When Jack Dorsey, founder of the very centralized social media platform, Twitter, posted this message about decentralized social media, our DWeb community took note:
Social media is populist and polarising; AI may be the opposite
Large language models elevate expert consensus and moderate views, in sharp contrast to social platforms
Social media algorithms don't allow us to understand or control what we see online and why... until now! Top scholars @jonathanstray.com and @noupside.bsky.social are sharing @mysky.social, a tool that allows users to adjust their feed’s priorities and explains why certain posts appear over others.
🎛️📲 Meet the algorithm you can actually control and understand
newpublic.substack.comDo our social media algorithms correctly reflect our values? Our new article published today in @pnas.org shows that the answer is often not, and that the content that gets promoted into their ranked feeds is often actively counter to our values.
🧵 On social media, we feel trapped in “filter bubbles” and “echo chambers.” Often, we see this as a problem with the algorithm. Our new essay argues the problem is the feed interface itself: it constrains our movement—all we can do is scroll. We lay out an alternative vision:
From Feeds to Trails
leaflet.pubDo our social media algorithms correctly reflect our values? Our new article published today in @pnas.org shows that the answer is often not, and that the content that gets promoted into their ranked feeds is often actively counter to our values.
