Media Log: Data Collection Edition

Hello, and welcome to my media log. I’ve decided to record Friday, January 27th; this day is a little different from most because it’s my day off. So, you will see an increase in the use of social media and digital apps compared to my previous media diary.  

Without further ado, here is my media log for January 27th:  

10:30 a.m. to 11 a.m. – Woke up and Watched TikTok 

When I woke up, I immediately watched TikTok. I watched dog content, stand-up comedy, and political content. The app likely collects data on what videos I like, what videos I save, what videos I watch through vs. scrolling past and my total watch time. That way, it can recommend videos that I will watch and show me advertisements I’m interested in. 

For example, I watched a Tiktok about a woman telling the audience how to style plus-size clothes. After the video, I was shown a post from Torrid, a plus-size clothing company. Think that’s a coincidence? I think not. 

11 a.m. to 11: 30 a.m- Browsed Social Media  

After I watched a few too many TikToks, I browsed my social media starting with Facebook. I typically don’t post but repost funny dog content. I’m part of my corgi groups on Facebook, so I’m often shown corgi-related posts. 

Facebook likely collects data on my interests, name, email address, age, location, workplace, and school. Facebook also knows my political party and some of my favorite brands. Facebook can use all that information to send to advertisers; that way, they can target my interests, so I’m more likely to engage with the ad. 

I then went on Instagram but only stayed on for a few minutes. Instagram likely collects the same data as Facebook, which can help them target me better. 

12:00 p.m. to 1:30 p.m – Watched Netflix 

Once I had my social media fix, I decided to watch some TV. I started watching the third season of Ozark.

Netflix likely collects data on what I watch, when I watch, and for how long. That way, Netflix can recommend shows I’m interested in. It also likely collects information about my name, address, age, and payment information. 

1:30 p.m. to 2:00 p.m – Ordered Uber Eats 

I got hungry later in the day and ordered sushi from Uber Eats. I’ve ordered sushi a lot, so Uber Eats immediately recommended the store to me when I opened the app. The app likely collects data on my location, payment history, payment type, email, age, and when and what I order. 

It can use that information to sell to advertisers. Since Uber Eats knows I like sushi and, more often than not, will order it for lunch, Uber Eats can do one of two things.

First, it can tell advertisers to target me around noon or so with sushi ads. Second, it can notify me directly through Uber Eats with a push notification that a certain sushi place is open and ready to be ordered for lunch. That way, I’m likely to be intrigued and buy from the app. 

2:00 p.m to 3:00 p.m- Watched YouTube 

I ate and watched YouTube videos. I watched several commentary videos by Danny Gonzalez and Drew Gooden. The app probably tracks what types of videos I watch, the creators I watch the most, and how long I watch videos. 

That way, YouTube can recommend videos that I’m more likely to watch and engage with. So by watching popular commentary videos, YouTube knows that I like commentary and will recommend similar channels like Dylan Is In Trouble and Casey Aonso.  

3:00 p.m. to 4:00 p.m- Read  

I’ve started reading books through Google books on my phone and laptop. Since I’m reading a book by Harlen Coben, the app has recommended me other books by him and similar crime novels. 

The app also tracks what I click on, when, and how long I stay on a page. So if I’m thinking about reading a different book, Google knows what genre to recommend. That way, I’m more likely to engage with the app and buy more books. 

4:00 p.m to 5:15 p.m- Yoga, Music, Fitness  

After reading, I decided to work out. To do yoga, I logged into an app called Yoga for Weight Loss. The app is also connected to Google fit, which logs calories, mileage, and heart points. 

I completed two different types of yoga workouts. However, by using the app, they have likely collected data about my weight, height, BMI, average workout time, and minutes completed. 

I then decided to walk a mile while listening to music and using Google fit. I’ve been listening to a lot of Everlast, and as such, YouTube Music recommended similar bands and songs while I went for my walk. 

YouTube Music likely collects data about who I listen to, the total amount of time, and my favorite genres. Google fit, on the other hand, most likely collected data about how long my walk was, how many steps I took, and the calories expanded. 

5:30 p.m to 6:00 p.m -Browsed Social Media 

After my workout, I browsed a few of my social media pages. I started with Twitter. I looked at the trending page and saw what people were talking about. Now, I don’t post or repost any content on Twitter. 

However, since Twitter pulls up what’s trending in South Carolina, I bet Twitter has collected data on my location, email address, and my phone number.  

I then went on Facebook again, but this time to see what my friends were up to. I saw that one of my friends got engaged, and I liked their post. I saw that another one of my friends went on vacation; I liked that post too. Since I liked their post, more of their content will come across my feed since Facebook knows I like seeing their content. 

6:00 p.m to 9:45 p.m- Watched Amazon Prime 

I’m not on Amazon Prime much, but I started re-watching the Hunger game series. Since I’m re-watching the Hunger Games, Amazon will likely recommend other movies and TV shows that are dystopian or based on books. 

Amazon likely collects information about my payment history, purchase orders, name, email address, home address, phone number, and interests. Since I have a student account, Amazon also collects information about the colleges I’ve gone to, my grade point average, the length of time I’ve been in college, and more.  

9:45 p.m to 10:30 p.m- Watched YouTube  

After watching the Hunger Games, I went on YouTube to watch AMSR content for a bit. I watched a number of videos by Nastya Slime and two videos from ASMR soap

YouTube collects, as I said before, information about what I watch. Although, since I have a student account, it also collects information about the colleges I’ve gone to and for how long, my student email address, my grade point average, and possibly classes I’ve taken since I had to send in my transcript.  

10:30 p.m to 11:00 p.m. – Watched Tiktok 

Before bed, I watched a number of TikToks. I watched videos containing dogs, pranks, a few food TikToks, and a number of slime Tiktoks. Since I watched and interacted with the videos by liking and saving them, TikTok is likely to show me similar videos. 


As I think about my social media, I realize that I don’t know exactly what information I’ve allowed social media platforms to share. I’ve mostly kept my profiles private so people can’t steal my photos and use them to start a fake account. However, I don’t know what I’ve inadvertently allowed companies to share about me. 

The information I do provide can certainly be used to target me for specific advertisements. For instance, Google knows my weight. Thus, Google can sell that information to advertisers like Torrid and Lane Bryant to advertise their new collections to me. 

Looking back at the log, I found that there were no new themes about how I use media. I utilize media to entertain me and escape from day-to-day activities as I’ve always had. I won’t be changing the way I interact with media. 

I don’t want to buy a VPN or use a private web browser to be on the internet. Not only is it not convenient, but there’s no 100% guarantee that my information will be safe if I complete these steps.  

As I see it, no company can guarantee digital privacy. So why should I pay ten dollars a month for a VPN, eight dollars a month for a password manager, and up to twenty dollars a year for anti-virus software when my data could be exposed anyway. For one year alone, that’s $236 that could have been better spent on rent, groceries, and other necessities. 

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