Continuous surveys across voice, video, links, and text | DATASPHERES AI - Dataspheres AI

One question, every channel The traditional survey has a shape: a form, a deadline, a spreadsheet. It also has a blind spot — most of what people can...

One question, every channel The traditional survey has a shape: a form, a deadline, a spreadsheet. It also has a blind spot — most of what people can tell you does not fit in a form. They can say it in a two-minute voice note, show it in a video, or point you at a talk that says it better than they would. A continuous multi-modal survey accepts all of it and keeps accepting it. The four intake lanes Voice. Recorded interviews and voice-agent conversations upload as audio. Diarized transcription separates the speakers and timestamps every turn — the same pipeline that split a 1h45m Senate hearing into ten attributed speakers in Module 3. The transcript, not the audio, is what you code. Uploaded video. Video files transcribe from their audio track and keep a poster frame in the library. Code them exactly like audio. Linked video. YouTube and conference recordings should stay where they live — link them instead. Native video analysis produces a summary you can code without re-hosting anyone’s content. Six of the seven sources in the working example entered this way. Text. Classic survey responses, journals, and documents keep working as in Module 2 — they simply share the codebook with everything above. One frame, live datasets The point of the shared codebook is that modality stops mattering at analysis time. A senator’s caution about chatbots and a panelist’s caution about cheating land in the same governance and integrity columns, with a stance attached — pro, con, neutral, or balanced. Coded segments accumulate in a dataset; a summary dataset counts stances per theme; and every chart bound to either one re-reads it at render time. See it running: the live thematic analysis codes Senate hearing audio and six panel videos into one frame, and its companion presentation draws every chart from the datasets — add rows and the deck changes. The discipline that makes it honest Continuous does not mean casual. Three rules keep a rolling corpus defensible. Code stances per segment, not per source — the same witness argues both sides of different questions, and collapsing that into one score is how nuance dies. Keep provenance on every row — source, speaker, timestamp — so any count can be walked back to a verbatim quote. And when a modality gives you weaker evidence — a video summary instead of a diarized transcript — say so in the row itself.