Reduced friction for adding places is a plausible reason for why 4square might have more venues, but what I was getting at is the order of magnitude of the difference.
10 MILLION places is a ton. Like I said above, thats like 250 NYC's. Even given 4square's reduced friction to add venues, the fact that they've probably launched in more cities, and inclusion of arbitrary venues ("Hey I checked in at the tree that's 10 paces west of my house!"),
I don't think 4square is lying. Now I'm just wondering how useful those venues are. (I am also pretending that Yelp has better than 10% coverage of venues that users care about). Incidentally, either way, you've got to think that 10mm venues has to wreck the data sparsity problem as well.
For reference, the venue count of 3 large american cities:
- NYC 47228
- SF 38656
- Chi 19079
I'd be surprised if Yelp had even 1.5mm venues. Would love if someone could corroborate/dispute this fact.
While there is certainly a disparity between the two and Yelp, I'd imagine that the "useful" venues (those that people want recommendations for) aren't your home or rainapololypse2011. Adding those into the dataset actually makes 4squares job _harder_ with respect to teasing meaningful data out of the dataset.
If my phone ever recommends your house though, I just may come a knockin'.
10 MILLION places is a ton. Like I said above, thats like 250 NYC's. Even given 4square's reduced friction to add venues, the fact that they've probably launched in more cities, and inclusion of arbitrary venues ("Hey I checked in at the tree that's 10 paces west of my house!"),
I don't think 4square is lying. Now I'm just wondering how useful those venues are. (I am also pretending that Yelp has better than 10% coverage of venues that users care about). Incidentally, either way, you've got to think that 10mm venues has to wreck the data sparsity problem as well.
For reference, the venue count of 3 large american cities:
- NYC 47228 - SF 38656 - Chi 19079
I'd be surprised if Yelp had even 1.5mm venues. Would love if someone could corroborate/dispute this fact. While there is certainly a disparity between the two and Yelp, I'd imagine that the "useful" venues (those that people want recommendations for) aren't your home or rainapololypse2011. Adding those into the dataset actually makes 4squares job _harder_ with respect to teasing meaningful data out of the dataset.
If my phone ever recommends your house though, I just may come a knockin'.