Below is the information that was captured on one of our team members, let’s call her Alex. We have included detailed information on exactly what we did in order to get the information to look the way it does. If you’d like to see what information has been collected on you, we highly recommend following along.
Alex began by asking Instagram for all of her information. To do this
go to the three bars are the top right-hand corner of the screen,
click on account activity, scroll to the bottom and request to
download all your information. After a few hours or days, Instagram
will send you an email letting you know that your download is ready.
After receiving the information, we sifted through it and decided that
the information about consumer tastes and in particular, reels, would
be most interesting. We took this data and converted it into a .csv
file.
Taking this .csv file, Alex pulled out analytics about the information
using SQL as well as created a word cloud to better visualize the
data. This process proved to be extremely convoluted as we had to
check multiple sources to find how to download the information, then
waited a long time to receive the information, and then finally had to
convert all of the data into a usable format.
Next, Alex asked Netflix for all of her information on what she has watched this year. This information was delivered within minutes and was much easier to parse through since it was already in a .csv format. The information that was in the file though only included the name of the movie or episode and when it was watched. In order to make this information more useful, Alex joined it with online Netflix tv shows and movies libraries that give more information about each show. This is the online dataset: https://www.kaggle.com/shivamb/netflix-shows that we used. From this point, we were able to draw analytics about what types of entertainment Alex like to consume.
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