Feed stuffing? Cascading corrections? Noise? All fun things to look at!
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No wait, I have to have an ingest error somewhere. Almost 50% delete rate can't be right.
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For one second I read mean deletes as “things people deleted because people were mean to them” and I was FASCINATED because finding that in social data would be a really interesting problem
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Yes, it would! I hope to look for that in the coming months, too!
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What am I looking at ?
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Top is fraction of messages in the sample stream that are deletes. Bottom is the total number of messages per minute. This one was over a few hours. Gonna actually dig deeper later -- I was just toying with the data before.
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