Tessera
Folgen

onur.ascigil

@asonur.bsky.social

Assistant Professor in Computer Science at Lancaster University

1 Posts209 Follower225 Folgt
Michał Król@harnen.bsky.social · 2y ago

@bsky.app grew tremendously over the last year. Recently, the platform introduced “starter packs” (SP) to help users bootstrap their social graph. Anybody can create these SPs. They’re lists of accounts (e.g., “people creating anime”) that others can then follow. 🧵1/11

Ignacio Castro@ignactro.eurosky.social · 2y ago

Twitter shows the risk of the centralised/monolithic/vertically integrated organisation approach with a benevolent dictator at the top: including the elusive nature of benevolence. 2 #IMC2024 papers examine Mastodon & Bluesky exploration of the design space of alternatives: [1/4]

ACM Internet Measurement Conference@acm-imc.bsky.social · 2y ago

We have an #IMC2024 paper on Bluesky itself: Looking AT the Blue Skies of Bluesky with Leon Balduf (Technical University of Darmstadt) & Saidu Sokoto (City, University of London) dl.acm.org/doi/10.1145/...

Paul Rohr@pevohr.bsky.social · 2y ago

Cool preprint leveraging access to the "data is public by default" architecture of the #ATprotocol to infer specific moderation practices by the bsky T+S team. They also calculated how little overlap there is between that team's work + the additive work being done by other labelers. Neat stuff!

For the official Bluesky Labeler, we observe two groups of labels: In the lower half of the plot, we find porn, nudity, corpse etc., which are applied within seconds, indicating automated systems. On the other hand, labels such as, e.g., spam, sexual-figurative, intolerant, and !takedown take longer to be applied, pointing to manual processes. ... It seems that heavy-handed moderation decisions such as removing data are deliberated instead of automated. This is reassuring, especially for the !takedown label having significant consequences for the affected users.In general, we find that label values generally show little overlap between the Bluesky Labeler and community Labelers, i.e., they seem to deal with mostly disjoint topics: Only 56,856 (1.8 %) objects are labeled by the Bluesky Labeler and any community Labeler. The Bluesky Labeler mostly labels NSFW content and upholds some community standards whereas the community Labelers seem to operate in specific niches. This is enabled by the flexibility (or lack of predefined) label values and user choice in how to react to labels.
bryan newbold@bnewbold.net · 2y ago

pretty interesting pre-print about bluesky/atproto! has an analysis of labeler response time (by label value), and digs in to feed service providers. the intro describes the atproto design goals and what is unique pretty well, IMO.