







W Social's tagline is "Trust Your Feed" but the company's landing page displays inflated engagement metrics - a misrepresentation that contradicts its own promise.
Elena Rossini 🌈 (@_elena@mastodon.social)
SCOOP: #WSocial is doctoring metrics on its homepage, inflating the number of comments on posts by prominent people on its network. I suppose a more accurate tagline for them should be "Trust your feed?" My article about it: "W Social, Fictional Metrics and the Beauty of Open Data" 🔗 : https://blog.elenarossini.com/w-social-fictional-metrics-and-the-beauty-of-open-data/ #blog #BigTech #EUBigTech #TEP #TrustedEuropeanPlatforms #TrustYourFeed
W — Trust your feed
We believe in the need for a global, trusted social media platform owned, run, and hosted in Europe. W is built on verified human users, transparency, privacy, and free speech.

W — Trust your feed
We believe in the need for a global, trusted social media platform owned, run, and hosted in Europe. W is built on verified human users, transparency, privacy, and free speech.

W — Trust your feed
We believe in the need for a global, trusted social media platform owned, run, and hosted in Europe. W is built on verified human users, transparency, privacy, and free speech.

Elena Rossini 🌈 (@_elena@mastodon.social)
Attached: 1 image 🚨 Important update about my latest #WSocial article 👀 A user on #ATproto cracked the code and came up with a reasonable explanation for the made up number of comments on W Social's homepage. The number next to the speech bubble (comment icon) are an "engagement metric": the sum of boosts and likes. It all makes sense now! https://blog.elenarossini.com/w-social-fictional-metrics-and-the-beauty-of-open-data/ (scroll down to the end of the article for the update)
W Social: Hello World!
Hello World! 🙂 This category is for discussing W Social, a new member on the AT-protocol federation. Launched in conjunction with the World Economic Forum in Davos on January 19, 2026, the project has sparked a lot of praise, interest, rumors and slander. In fact, our social media monitoring console registered 1 billion post views (across all the main social media) for posts mentioning #wsocial within the first week. As I write this, W Social is not yet open for business. There i...

Value misalignment in X’s feed algorithm is a reflection of value tensions in engagement
Social media feed algorithms rank content that is purported to be preferred by users, but the engagement behaviors that drive these algorithms are (at best) indirect proxies for users’ explicitly self-stated values. Are the resulting feeds value aligned, and if not, why? We investigate this question by annotating the basic human values expressed in participants’ X (Twitter) feeds (N = 715 US users), analyzing the relationship between the posts’ value expressions and the posts’ amplification in the ranked “For You” Page feed, and then comparing the amplified values to users’ own values. We observe that the inventory of posts from followed accounts reflects users’ self-stated values—but that there is an overall negative correlation (misalignment) between users’ explicit values and the value expressions the algorithm is more likely to amplify. We turn to engagement behavior to understand this misalignment and observe that users’ engagement behaviors can be misaligned with their stated values—likely causing the algorithm to learn and reflect these misaligned values. We also detect partisan differences consistent with this theory: While the algorithm amplifies values negatively correlated with both Democrats’ and Republicans’ self-stated values, they are more misaligned for Democrats. And in fact replying, a heavily weighted form of engagement, is associated with values that are less aligned for both Democrats’ and Republicans’ self-stated values, and is even more misaligned for Democrats. Taken together, these findings offer a glimpse into the tensions between the values that people hold and those that provoke reactions, and how these value tensions can produce misaligned outcomes.

Value misalignment in X’s feed algorithm is a reflection of value tensions in engagement
Social media feed algorithms rank content that is purported to be preferred by users, but the engagement behaviors that drive these algorithms are (at best) indirect proxies for users’ explicitly self-stated values. Are the resulting feeds value aligned, and if not, why? We investigate this question by annotating the basic human values expressed in participants’ X (Twitter) feeds (N = 715 US users), analyzing the relationship between the posts’ value expressions and the posts’ amplification in the ranked “For You” Page feed, and then comparing the amplified values to users’ own values. We observe that the inventory of posts from followed accounts reflects users’ self-stated values—but that there is an overall negative correlation (misalignment) between users’ explicit values and the value expressions the algorithm is more likely to amplify. We turn to engagement behavior to understand this misalignment and observe that users’ engagement behaviors can be misaligned with their stated values—likely causing the algorithm to learn and reflect these misaligned values. We also detect partisan differences consistent with this theory: While the algorithm amplifies values negatively correlated with both Democrats’ and Republicans’ self-stated values, they are more misaligned for Democrats. And in fact replying, a heavily weighted form of engagement, is associated with values that are less aligned for both Democrats’ and Republicans’ self-stated values, and is even more misaligned for Democrats. Taken together, these findings offer a glimpse into the tensions between the values that people hold and those that provoke reactions, and how these value tensions can produce misaligned outcomes.

Do links hurt news publishers on Twitter? Our analysis suggests yes
Engagement for tweets from @nytimes (53 million followers) is dwarfed by engagement for tweets from @GlobeEyeNews (866,000 followers).

The Untold Story About W Social: Unconventional Beginnings, Strategic Pitches and Conflicting Signals
A deep dive into the origin story of W Social, an analysis of the strategic arguments they have been using to appeal to government officials, media companies and advertisers... and the discussion of conflicting signals they have been sending

The Untold Story About W Social: Unconventional Beginnings, Strategic Pitches and Conflicting Signals
A deep dive into the origin story of W Social, an analysis of the strategic arguments they have been using to appeal to government officials, media companies and advertisers... and the discussion of conflicting signals they have been sending

The thought occurred to me (belatedly) that maybe there are other accounts on the promotional website that aren’t actually on W Social yet. Right now, wsocial.news shows me 4 users who are indeed on W Social and 3 who aren’t: @london.gov.uk, @beate.neos.eu, and @teresaribera.ec.europa.eu.
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@london.gov.uk is still on wsocial.news and is still not actually on W Social. It’s been long enough to really make it look like it could be the Greta Thunberg thing all over again Sources: pdsls.dev/at://did:plc:axuvbckddrg7lwlp… blog.elenarossini.com/the-untold-story-about-w-soci…
Do 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.
Do 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.
LATEST: on #WSocial's website, comment counts for posts by prominent users are incorrectly displayed, showing artificially elevated numbers. @opfuchs.gay came up with an interesting theory for it. "W Social, Fictional Metrics and the Beauty of Open Data": blog.elenarossini.com/w-social-fictional-metrics-an…
W Social, Fictional Metrics and the Beauty of Open Data
blog.elenarossini.com✨New paper out @nature.com ✨ For 8 weeks around the 2024 US election, we randomly assigned 2,000 people to use social media algos we built ourselves. Do engagement-based algorithms amplify intergroup, moral & emotional (IME) content—and does that distort how we see political norms? 🧵🔗 👇