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What do we want? Unbiased reporting! When do we want it? During protests!
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Nov. 21, 2013, 2:49 p.m.
LINK: medium.com  ➚   |   Posted by: Joshua Benton   |   November 21, 2013

That’s the claim of this piece by Medium product scientist Pete Davies, which goes into why they prefer to push past vanity metrics that create giant PR-friendly numbers.

We’ve crossed a point at which the availability of data has exceeded what’s required for quality metrics. Most data scientists that I meet tell me that they’re gathering way more data than they can ever hope to use. And yet, in many cases, they still don’t have useful metrics…

I think of competing for users’ attention as a zero-sum game. Thanks to hardware innovation, there is barely a moment left in the waking day that hasn’t been claimed by (in no particular order) books, social networks, TV, and games. It’s amazing that we have time for our jobs and families.

We measure every user interaction with every post. Most of this is done by periodically recording scroll positions. We pipe this data into our data warehouse, where offline processing aggregates the time spent reading (or our best guess of it): we infer when a reader started reading, when they paused, and when they stopped altogether. The methodology allows us to correct for periods of inactivity (such as having a post open in a different tab, walking the dog, or checking your phone).

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What do we want? Unbiased reporting! When do we want it? During protests!
Not all protests get treated equally. Stories about women’s marches and anti-Trump protests give more voice to the protesters than those about Black Lives Matter and other anti-racism protests.
Instagram is busy fact-checking memes and rainbow hills while leaving political lies alone
Plus: Emphasizing a publisher’s name on social doesn’t seem to impact readers’ misinfo radar much one way or the other.
Is this video “missing context,” “transformed,” or “edited”? This effort wants to standardize how we categorize visual misinformation
MediaReview wants to turn the mishmash vocabulary around manipulated photos and video into something structured.