Zovda
Creators post the same clip to several places, often within minutes. A dataset that counts each posting as one item reports an audience that is partly the same people, counted repeatedly.
The volume is real and the reach is not.
Volume, reach, and attention are three numbers
Posting counts measure distribution. Unique content measures intent. Unique authors measure reach, roughly. Reporting only the first turns a distribution channel into a popular movement.
Compute all three and publish them side by side.
Matching across postings
The text is often identical, the media is often identical, and the timestamp is within minutes. A fingerprint on text plus media plus a short time window catches most of it.
Loosen the window and you merge separate campaigns. Tighten it and you miss the delayed copy.
Engagement does not add up
The same audience sees the same clip in two places and engages once. Summing engagement across postings double-counts the loudest people, which is exactly the number most dashboards show.
Keep the group, not just the flag
Instead of deleting duplicates, group them: one canonical item plus its postings. Then a campaign report can count postings and a reach report can count groups.
Zovda assembles these collections through Datuva, where the canonical item and its postings stay linked. The social media data collection shows the fields.
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