StreamRooms detects whether a Kick channel's viewer count is real using multi-point time analysis. A stream is scanned at dozens of different points in time; the ratio between chat messages and views is compared with the channel's own historical median. The result shows whether the stream showed healthy participation detected while it was genuinely live, not while on the standby screen.
Throughout a stream, the system evaluates the cumulative participation rate (chat/view ratio from the start up to that moment) at many points in time, along with time windows of different lengths (short, medium and long term), separately. If one signal looks low while another is normal, no average is taken and no smoothing is applied that would hide the real situation.
Each finding gets a confidence level (low/medium/high) based on the channel's overall chatter quality. If the channel's chat community is already full of suspicious accounts, no "definite bot" conclusion is reached from a single finding; this is an extra verification layer that reduces false positives.
Bot detection is available both in the public channel analysis tool (free, no login) and in the streamer dashboard. Once a stream has been deep-scanned, the result is stored permanently and shown instantly when the same stream is queried again.
StreamRooms scans a stream at dozens of different points in time and compares the cumulative participation rate with several time windows. The ratio between chat messages and views is compared with the channel's own historical median; the results are weighted to detect unreal viewer increases.
When a deep scan of a channel is requested in the public analysis tool, the result is usually ready within 30–90 seconds and is stored permanently.
No. The system evaluates several signals from different time windows together and adds a confidence level based on the channel's overall data quality; a single low measurement doesn't make a definite result on its own.
Setup takes a few minutes and needs no extra hardware.
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