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Social Forum federato con il resto del mondo. Non contano le istanze, contano le persone

So, is it getting quieter here in the #Fediverse; is it even dying?

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    @mapache @badgefed looks promising! looking forward to trying this out.(I guess there may be an issue with the acknowledgement on the Mastodon side as this shows pending?)
  • Guten Morgen #Fediverse.

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    @marzlberger Merry Christmas to you!
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    The major feature in v3.2.0 of Ktistec is thread analysis. The previous release, v3.1.2, added support for viewing threads from Lemmy communities. I follow the Open Source community, which leads to many large threads. The thread on FFMpeg and Google has 112 posts and is still growing.Thread analysis helps me navigate these extensive conversations. It includes: top contributors, a timeline histogram, and notable branches.The analysis applies several heuristics to identify interesting branches of the main thread. “Interesting” is subjective, but the algorithm currently looks for sudden bursts of activity and highlights those areas. Ktistec uses this to create a table of contents that links directly to those branches. Clicking on one of these links takes you to a branch-only view that focuses on the selected part of the thread.It's fast—I anticipated needing to cache analyses, but analyzing a thread with over 400 posts takes only about 50 milliseconds on my production server.Figure 1: Screenshot of the final design. Notable branches link to subsets of the thread.This release also addresses an object visibility regression that was introduced in a previous version.Full ChangelogAddedThread analysis that displays key participants, a timeline histogram, and notable branchesNew MCP tools: analyze_thread and get_threadFocal point rendering support for image attachmentsFixedRegression in object visibility affecting replies to threadsChangedEnhanced MCP tool details for likes, dislikes, and announcesImproved cookie security.#ktistec #fediverse #activitypub #crystallang
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    I’ve been thinking about discovering underappreciated Lemmy instances. GitHub’s awesome-lemmy-instances used to serve a similar purpose, but it hasn’t been updated in a long time, and I haven’t found anything else like it. I got the idea from this post about finding decentralized communities in the Fediverse. I’m thinking of a Lemmy bot that tracks Lemmy instances, calculates the average number of active users and standard deviation, and identifies instances with activity below the average plus two standard deviations. It would then rank these underutilized instances by performance metrics like uptime and response time, and periodically update a curated list on Lemmy to guide users toward instances that could use more participation. I'd love feedback on how you would go about doing something like this. And specifically how to rank by performance.