“We can look at random samples of raters, and if they're rating things very differently than self-selected, possibly malicious raters, then that's a very important signal”
Community Notes team · TED Tech · How Community Notes reduce viral misinformation | Jay Baxter and Keith Coleman
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What was described
sample random raters and flag those whose ratings differ sharply from the self-selected pool
Said nearby on the same subject
“We flag those things that an underwriter might have missed. We flag those discrepancies, the yellow flags, the red flags, the green flags that are sometimes buried in that information.”
“We look for raters who have rated things really similarly in the past, and actually, we might treat them as the same person just to limit the influence of really similar behavior”
“Set up Rate My Clinic where people can get assessments done, find out how they compare on each of those different benchmarks. And importantly, recommendations on how to improve”