5 ms·

Here’s an interesting article on Tinder’s solution to this problem: https://robertheaton.com/2018/07/09/how-tinder-keeps-your-location-a-bit-private/ https://ro

Here’s an interesting article on Tinder’s solution to this problem: https://robertheaton.com/2018/07/09/how-tinder-keeps-your-location-a-bit-private/ https://robertheaton.com/2018/07/09/how-tinder-keeps-your-lo...

petre 6y ago
It can be easier. One could geohash the location with a certain precision, say 5 = ±2.4 km and only display people in that geohash and the neigbouring geohashes. https://en.m.wikipedia.org/wiki/Geohash https://en.m.wikipedia.org/wiki/Geohash
- deleted 6y ago
  [deleted]
- ericpauley 6y ago
  The functional component of this technique is still just quantization (as in the parent). One might argue that this is actually more complicated.
randyrand 6y ago
The article asks why they don’t just use grid snapping only. If you lived on a boundary it would be very clear because your location would change very often, perhaps just by walking to the kitchen.
- ape4 6y ago
  It could use neighborhood. Use GPS to locate your neighborhood then give your location as the townhall or central park or whatever in that area.
  - tharkun__ 6y ago
    Changing what you use as the boundary doesn't change the fact that if you're close enough to the actual boundary, you will jump a lot. So you have to go quite large with the boundary for it to limit the pinpointing. Having larger areas within your boundaries makes the feature much less 'useful' though. Which granularity: Harlem/Hell's Kitchen etc? West Harlem/East Harlem etc? Manhattan/Long Island? New York/New Jersey etc.? Feature wise you would probably want at least something like Harlem/Hell's kitchen granularity and there are unfortunately enough people living on the borders of all of these that you could pinpoint those just from GPS inaccuracies.
- shawnz 6y ago
  Perhaps you could add some sort of hysteresis such that it continues to report you as being in the previous grid square unless you go >1/2 a grid square distance away from it

petre 6y ago

It can be easier. One could geohash the location with a certain precision, say 5 = ±2.4 km and only display people in that geohash and the neigbouring geohashes. https://en.m.wikipedia.org/wiki/Geohash https://en.m.wikipedia.org/wiki/Geohash

deleted 6y ago
[deleted]
ericpauley 6y ago
The functional component of this technique is still just quantization (as in the parent). One might argue that this is actually more complicated.

randyrand 6y ago

The article asks why they don’t just use grid snapping only. If you lived on a boundary it would be very clear because your location would change very often, perhaps just by walking to the kitchen.

ape4 6y ago
It could use neighborhood. Use GPS to locate your neighborhood then give your location as the townhall or central park or whatever in that area.
- tharkun__ 6y ago
  Changing what you use as the boundary doesn't change the fact that if you're close enough to the actual boundary, you will jump a lot. So you have to go quite large with the boundary for it to limit the pinpointing. Having larger areas within your boundaries makes the feature much less 'useful' though. Which granularity: Harlem/Hell's Kitchen etc? West Harlem/East Harlem etc? Manhattan/Long Island? New York/New Jersey etc.? Feature wise you would probably want at least something like Harlem/Hell's kitchen granularity and there are unfortunately enough people living on the borders of all of these that you could pinpoint those just from GPS inaccuracies.
shawnz 6y ago
Perhaps you could add some sort of hysteresis such that it continues to report you as being in the previous grid square unless you go >1/2 a grid square distance away from it