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User-mining: Start at the gym, end up at a bar?

96 pointsby rwalianyalmost 15 years ago

9 comments

drc1912almost 15 years ago
Can you please tell us a little bit about the data/population that served as the basis of this analysis (ex: how big is total population of data set, how big is the subset of users who went to both gym and park, etc). It would help us better provide feedback and understand the your results.
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randomwalkeralmost 15 years ago
The restaurant data is the only one that is at odds with intuition, and strongly so. Why would Thursday be 3.5x more popular than Wednesday? Without an explanation, I'm more willing to believe that there was a data anomaly.
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Herald_MJalmost 15 years ago
Am i infer that half-way between wednesday and thursday (midnight) that the check-in rate for restaurants is half way between the two (~450)?<p>Silly choice of graph type.
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xiaomaalmost 15 years ago
I'm amazed so few people are at the parks in the mornings. I always thought that they were crammed with people walking their animals, exercising, etc... from around 5:30 to 8:00 am.<p>I guess people there like to sleep in.
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festivusralmost 15 years ago
Has any study been done about the likelihood of people to check-in with one of these social apps? If someone checks-in at the gym on Monday, are they going to be less likely to check in again on Tuesday? People I know seem to check-in when they are subtly bragging about what they're doing, so is it likely they'll check-in at a non-trendy restaurant on a Tuesday evening?
rwalianyalmost 15 years ago
Updated graph on gym usage by hour: <a href="http://simplyryan.files.wordpress.com/2010/07/gymhour.png" rel="nofollow">http://simplyryan.files.wordpress.com/2010/07/gymhour.png</a>
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spectrealmost 15 years ago
Any idea why there are two peaks for bar attendance at 8am and 10am?
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texasicealmost 15 years ago
Nice work.
revanthvalmost 15 years ago
This awesome.Having this kind of analysis really helps
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