Data Storytelling Studio 2020

Data Diary for 02/22

Chatting

Chatted with friends and family on WhatsApp, Messenger 

iMessage, sent and received pictures

Posted stories on Instagram, shared location

Sent an email to a TA regarding a problem set question on outlook

Sent my visa documents to company representatives in London and Poland on gmail

Moving around town

Credit card used to buy lunch at Cava 

Added money to starbucks account and bought coffee at Starbucks Kendall 

Credit card amazon to order supplies, used delivery address

Credit card used to order food and drinks, used delivery address

Credit card used to uber to restaurant, club, and back 

Online

Bloomberg, WSJ, Facebook, apartment rentals, Stellar, Xfinity, Netflix

Other

Chatted with Alexa to turn on Spotify, asked Alexa about weather

Chatting with people:

My day started with responding to messages on Messenger and iMessage, as well as checking my email to make a to-do list of emails to respond to during the day. In order to communicate with my friends and family, I use Facebook Messenger and iMessage heavily on a daily basis. I would say 70% of my text communication is on Messenger, 10% is on iMessage, and 10% is on other platforms; besides Messenger and iMessage, I also use Gmail, Slack, and GroupMe to communicate throughout the day. I use Gmail for all of my email services, including my MIT email which forwards itself to my Gmail inbox. Throughout the day, I also checked GroupMe, which is what my living group uses to communicate with each other. My UROP uses Slack, though the volume of messages there is fairly low, and I didn’t end up using it today. 

Using Facebook’s Messenger, Apple’s iMessage, Google’s Gmail, and Microsoft’s GroupMe on a daily basis means that I rely on four of the biggest technology companies for my basic communication. They each have my long-standing personal data, as well as temporary location data throughout the day.

Moving around town:

I live in Burton Conner, where there are cameras at the entrances, and residents are required to tap in. I know that the Burton Conner security cameras saw me walk out around 8:30 a.m. At around 9:00, I paid for Dunkin with my credit card. At 11:00, I got Cava in Kendall Square with a good friend of mine and used Apple Pay to foot the bill. These three events paint a pretty good picture of where I spent my morning.

In the early evening around 5:00 p.m., I tapped my ID into McCormick Dance Studio for the first two hours of my dance practice. There are also cameras at the McCormick entrance. At 8:00, I tapped into the Z Center for more dance practice. Finally, at around 9:30 p.m., I walked back to Burton Conner where I tapped in again and was also visible in the security cameras.

Although I didn’t use any form of transit besides my feet today, my location was still very well documented because of the large quantity of tap access doors on campus, as well as the use of digital payment systems.

Getting online:

Today I read the news on the New York Times online, did work on Stellar, Google Docs, Google Sheets, and WordPress, and casually browsed Instagram, YouTube, and Twitter. For all of these sites, I have an account with my basic personal information.

I use my overarching G Suite account for YouTube, Docs, and Sheets, so all of this information is also tied along with my Gmail. For Stellar, I have to use my MIT authentication to log on, associating all of that data with my collegiate footprint. My Instagram is tied to my Facebook, and my Twitter is also linked to my other social accounts. Thinking about this really highlights how associated all of my social accounts are and how connected each node of my data log is.

Other things:

Even when I’m not using applications on my phone, some of them are collecting data and my location from me. I also have a Microsoft Cortana smart speaker in my room, collecting all sorts of data about what I’m saying, when I’m waking up, and what I’m listening to. This exercise has led me to realize that if you combined all of the data I leave behind in a day, you can paint a really accurate picture of what I’m up to.

Chatting with People

As usual, I used emails and Slack a lot throughout the day, mostly to schedule meetings and coordinate work, but also to just get in touch with friends. I texted friends with WhatsApp and, despite it claims end-to-end encryption, I also use Signal since it should be a more secure and privacy-focused app. Even if the content of the messages was not collected as plain text, it is most likely that encrypted information was still collected and logged, as well as my GPS position and time of the day. 

Moving Around Town

I walked from my dorm to the main campus, but my location has most likely been captured by apps running the background anyway. Later in the day, I took the T to Harvard and my travel got logged when swiping my T pass, while my face got caught from security cameras throughout the station. Throughout the day I also swiped my MIT ID Card to pay for food and access buildings, leaving traces around campus about my location and purchases.

Getting Online

I stayed online for most of the day with my Google account logged in, using a multitude of applications which must have been captured by Google. I also logged into specific websites that require registration such as news sites like The New York Times, Bloomberg but also my MIT and Harvard accounts. Throughout the day I checked social media, scrolling through my feed. This allowed these websites to track a wide range of information, from my position to the links I clicked, posts I liked and videos I watched, adding up to the user profile they already have on me.

Other Things

I am pretty sure there is a whole range of apps and systems collecting my information with me not even realizing it. For instance, I might have granted too many permissions to a few apps, which are collecting a wide range of data even in the background.