About EdgeStories

EdgeStories is a publication, not a product. It does original research into the data between people — who follows whom, who thanks whom, how ties form and fade — and publishes what it finds as visual essays. Think of it as closer to a magazine of data journalism than to an app: there is nothing to sign up for and nothing to log in to.

Most analysis of social data looks at the nodes: the people, their follower counts, their posts. The richest signals live on the edges instead — the relationships themselves, when they began, whether they were returned, and what shape they add up to. Each story picks one public record of those edges and reads all of it.

Where the data comes from

Sources are chosen per story by what the question needs. Durable public archives come first — Wikipedia logs, OpenAlex, Crossref, GH Archive, Hacker News — because they cannot be repriced or withdrawn. Bluesky is used when a story needs timestamps on when a connection was made or broken, because it is the only network that publishes them. Every story states its sources, sample sizes, and caveats alongside the findings rather than in a footnote.

How stories are made

• Aggregate by default — private individuals only ever appear as rates, distributions, and structures — never as named pairs
• Measured, not illustrative — every number published was computed from the data; nothing is rounded up or invented for effect
• Methods travel with the piece — sources, truncation, and any use of language models are disclosed where the reader will see them
• Corrections in public — errors are fixed in place with a dated note explaining what changed

EdgeStories is written and built by Kaiyu Hsu. To get the next story, leave an email in the subscribe form on the home page; to say something about one, see the contact page.