👁️ Noticed: community attention (the 9-year moat)

Noticed measures attention: how much the community looked at and engaged with public Stolen Stuff Hawaii posts, reported as the SSH Community Attention Index. It is the deepest signal in the tool, with a measured history back to July 2017, nine years of community attention that no other product can replicate.

What it is, and when it begins

Noticed reflects aggregate public attention across the SSH network (Facebook, Instagram, YouTube, TikTok, X, and SSH websites), distilled into the Community Attention Index, a 0-100 indicator of SSH's own design. Platform-specific analytics are aggregated and transformed into that indicator and never republished; no per-platform figure appears anywhere in the product. It is an audience signal, shaped by how many people follow and engage, not a tally of incidents. The daily engagement record begins July 2017, with dated audience snapshots from October 2015 and the monthly index series from 2018.

What the SSH Signal page shows

The page opens with the index at a glance and the month in context: where the month stood among all months on file, how it compared with the same month a year earlier, and how broadly attention moved across tracked areas. Below that sit the month's topics (with a topic search and per-topic trends), the topics whose share of attention rose or eased, where attention concentrated by area, the index's full monthly history and typical-year profile, and the community's own reporting rhythm, including recaps of past holiday windows.

What it can tell you

What a community paid attention to, and when attention spiked (a widely-shared post, a viral incident). Read alongside the incident signals, it shows the difference between what happened and what people noticed.

What it cannot tell you

It is never an incident count. A high index reading means a large, engaged audience was looking, not that more crime occurred. Treating attention as incidence is the most common way to misread this signal, so the tool always keeps it on its own axis and labels it as attention.