My personal data from 10 apps

August 17, 2019

The EU’s General Data Protection Regulation (GDPR) law has prompted many web companies to allow its users to easily download (a subset of) the personal data they have stored. I was curious what information was held by the apps that I use (and what they would provide), so I requested data from the companies below (plots below, GitHub code).

  1. Spotify - streaming history, playlists, search queries (only last 90 days)
  2. Twitter - tweets, likes, ad impressions/engagements, messages
  3. Amazon - orders, items (missing browsing history available for amazon.co.uk)
  4. Facebook - likes, comments, messages, search history (missing ad impressions)
  5. Apple - podcast listening history, app downloads, every wifi network I’ve connected to (missing location data)
  6. LinkedIn - connections, messages, searches
  7. Uber - cost, locations for every ride
  8. Venmo - all transactions
  9. Bank of America - all credit card transactions
  10. Tinder - messages, (daily aggregate numbers of) matches and swipes

I also requested data from Airbnb (denied), Bumble (denied), CoffeeMeetsBagel (waiting 3+ weeks), Google (waiting 3+ weeks), Lyft (denied), and Yelp (nothing interesting provided, missing browsing history).

   

Figure 1. Some of my favorite podcasts over time. (Data source: Apple)

   

Figure 2. Changes in the relative amount I've spent on different cuisines. (Data source: Bank of America)

   

Figure 3. The bands I have listened to most recently (Data source: Spotify)

   

Figure 4. Over time, I have been using Facebook less for friends and more for memes. (Data source: Facebook)

   

Figure 5. Word cloud indicating the words I use most frequently in my tweets. (Data source: Twitter)

   

Figure 6. Rate of Tinder matches while I'm in different cities. (Data source: Tinder)

   

Figure 7. Word cloud indicating the words and emojis that are most common in my Venmo transacations. (Data source: Venmo)

   

Figure 8. Cost of my Uber rides per minute in different cities. (Data source: Uber)

   

Figure 9. Number of my LinkedIn connections classified in each profession. (Data source: LinkedIn)

   

Figure 10. Amount I've spent on Amazon in different categories. (Data source: Amazon)

       

Figure A1. Play counts for my favorite podcasts. (Data source: Apple)

   

Figure A2i. How much I've spent on different cuisines (Data source: Bank of America)

   

Figure A2ii. How much I've spent on different things over time (Data source: Bank of America)

   

Figure A2iii. Total amount I've spent on different cuisines on my credit cards since 2013. (Data source: Bank of America)

   

Figure A3i. Amount of Spotify I've listened to each day. (Data source: Spotify)

   

Figure A3ii. Songs I've played most recently. (Data source: Spotify)

   

Figure A3iii. Artists I've listened to a lot in June and July 2019. (Data source: Spotify)

   

Figure A3iv. Number of songs from each artist that I have favorited. (Data source: Spotify)

   

Figure A5i. Frequency of different words in the tweets I like. (Data source: Twitter)

   

Figure A5ii. Number of times I've liked tweets from different accounts. Fairly few non-neuroscientists(*). (Data source: Twitter)

   

Figure A7i. Number of times different words or emojis (:emoji:) appear in my venmo transactions. (Data source: Venmo)

   

Figure A7ii. Amount of money I've transferred on Venmo over time. (Data source: Venmo)

   

Figure A8i. Cost of UberX per mile in different cities. (Data source: Uber)

   

Figure A8ii. Cost of my UberX rides per minute over time in California. (Data source: Uber)