The Ledger

Every statement that passed quotation and attribution checks. Mix any filter with any other: certainty 1/5, debate potential 5/5, or both at once.

clear all ✕

why aren't all 10 resolved? a statement only gets an assessment when the public record can support or contradict it. opinions and what-ifs never can, and 0 checkable ones are still open, waiting for their date. predictions held up or didn't; assertions are supported or contradicted. on every card: ▮▮▮▮▮ certainty · ▮▮▮▮▮ debate potential. speakers are clickable

Assertion Not checkable as stated
Foursquare data reveals 73% of venue visits are to previously visited places
“We've seen that 73% of the time a person is going to a place that they've already been to, or 62% of the time they're going to a place that someone in their social network has been to before.”
Blake Shaw Dec 5, 2013 ▶ 9:19 Blake Shaw, Foursquare // Data Driven NYC 20 // Nov 2013
Insight
Effective location machine learning requires mapping raw coordinates to contextual venues
“You can't do machine learning with lat-longs.”
Blake Shaw Dec 5, 2013 ▶ 10:14 Blake Shaw, Foursquare // Data Driven NYC 20 // Nov 2013
Disclosure
Foursquare commits to not sharing raw user location data with third parties
“We're not going to share your data with anybody without, you know we're just not going to share your data.”
Blake Shaw Dec 5, 2013 ▶ 15:08 Blake Shaw, Foursquare // Data Driven NYC 20 // Nov 2013
Assertion Not checkable as stated
Faking Foursquare accounts with verified GPS trails and social graphs remains difficult
“It's really hard to fake a user with a, like, verified GPS trail going to a business, like, and having these real friends on a social network. You know, like, that's just, it's a very hard thing to fake at the moment, although I, I'm upset to say that, because…”
Blake Shaw Dec 5, 2013 ▶ 19:52 Blake Shaw, Foursquare // Data Driven NYC 20 // Nov 2013
Assertion Not checkable as stated
Foursquare reports 40 million registered users and 4.5 billion total check-ins
“We're, we have over forty million registered users. We're aware of fifty-five million places all over the world. We've collected 4.5 billion check-ins. And we get about six million check-ins per day.”
Blake Shaw Dec 5, 2013 ▶ 1:12 Blake Shaw, Foursquare // Data Driven NYC 20 // Nov 2013
Disclosure
Foursquare launches automated location recommendations that require no manual check-ins
“The idea, right, is you walk into a venue, and without having to do anything, you get a notification like this on your phone.”
Blake Shaw Dec 5, 2013 ▶ 5:00 Blake Shaw, Foursquare // Data Driven NYC 20 // Nov 2013
Disclosure
Foursquare triggers automated notifications only when users enter unfamiliar territory
“You know, walk into a neighborhood or a place, and we make sure that you don't miss the most important information about the place that you're at, but only if you're in unfamiliar territory.”
Blake Shaw Dec 5, 2013 ▶ 5:43 Blake Shaw, Foursquare // Data Driven NYC 20 // Nov 2013
Assertion Not publicly verifiable
Foursquare claims its background contextual notifications use under 1% battery hourly
“Less than one percent per hour is the, is what it does.”
Blake Shaw Dec 5, 2013 ▶ 6:44 Blake Shaw, Foursquare // Data Driven NYC 20 // Nov 2013
Assertion Not checkable as stated
18% of users shown a Foursquare Explore recommendation check in within days
“With our recommendation product, Explore, 18% of people who see a result in Explore check in there within the first three days.”
Blake Shaw Dec 5, 2013 ▶ 13:21 Blake Shaw, Foursquare // Data Driven NYC 20 // Nov 2013
Disclosure
Foursquare built NLP models to extract venue recommendations and sentiment from tips
“We've built, you know, sort of NLP models that can read You know, text and extract these key recommendations and figure out their sentiment.”
Blake Shaw Dec 5, 2013 ▶ 11:48 Blake Shaw, Foursquare // Data Driven NYC 20 // Nov 2013
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