User-mining: Start at the gym, end up at a bar?
simplyryan.com
User-mining: Start at the gym, end up at a bar?
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Re: User-mining: Start at the gym, end up at a bar?
#2The 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.
Re: User-mining: Start at the gym, end up at a bar?
#3The 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.
The data suggests that Thursday night Tapas bar/restaurants are very popular and that is included under "restaurants" according to yelp.com.
Re: User-mining: Start at the gym, end up at a bar?
#4This awesome.Having this kind of analysis really helps
Re: User-mining: Start at the gym, end up at a bar?
#5[deleted]
Re: User-mining: Start at the gym, end up at a bar?
#6Can 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.
Re: User-mining: Start at the gym, end up at a bar?
#7The 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.
Thursday is a _HUGE_ night at bars (and restaurants with bars) for college students. A lot of kids will take advantage of happy hour pricing on Thursday night and lax attendance policy on Friday morning.
This is anecdotal and I don't have data to support my claim (although someone can probably find something on Google).
Re: User-mining: Start at the gym, end up at a bar?
#8Can 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.
The data is from March 15th to May 1st (~45 days). It is a noisy estimation based on foursquare and twitter location check-ins (estimated samples from a population of about 100k users in San Francisco, CA with a technology bias). I haven't analyzed user-specific data, such as who went to both venues. I am open to suggestions on future analysis.
Re: User-mining: Start at the gym, end up at a bar?
#9The 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.
Thursday is a _HUGE_ night at bars (and restaurants with bars) for college students. A lot of kids will take advantage of happy hour pricing on Thursday night and lax attendance policy on Friday morning. This is anecdotal and I don't have data to support my claim (although someone can probably find something on Google).
Yeah, thirsty thursday (college student here)
Re: User-mining: Start at the gym, end up at a bar?
#10The 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.
You're making a critical logical mistake - assuming a data anomaly when you don't know anything about the field, but you take a 5-second check with your own intuition, and can't find an explanation.
You've never heard "Thursday's the new Friday"? College kids and young employeds party hearty on Thursdays now. It started in the early 2000's.
Uncle Google shows that even the NYT knows about it: http://www.google.com/search?q=thursdays%20the%20new%20frida...
Remember: just because you can't figure out the reason intuitively, and immediately, doesn't mean there isn't one.