Tag Archives: data collection

Data Collection (Noah Fischer)

For my data collection I decided to track the amount of steps I take for a week. On the iPhone there is the health app that tracks everything that is related to your health from steps to the amount of flights climbed in a day. Walking is an everyday thing, and I was curious on how many steps I actually take throughout the week. 

If Someone was to look at my data, they can probably assume that I don’t really do crazy amounts of walking during the week, except for a few occasions. They can also jump to a conclusion that I don’t have school two days of the week and during those two days I’m just relaxing and enjoying my day off.

    The three days that probably grabs the person’s attention are Thursday, Friday and Sunday. Friday and Saturday are the lowest because those two days would be the days I don’t have school, and I prefer to stay home, especially in this weather. But Thursday November 7th was the highest because those were one of those days with the occasional “adventure” with my friends after school.

    During the week of tracking my data, I only had three days with more than 10,000 steps. Thursday, November 7th was when I went to the city after class with my friends and totaled about 21,000 steps. The next day that is high in steps was on Monday the 11th where I had around 15,000 steps because once again I also went to the city with my friends. Wednesday was a total of 11,500 steps because I had went to work, the building I work at is about a mile walk there and back from the nearest train station.

I chose to track my steps because growing up I always tried to track my steps with those pedometers. I would always end up cheating and shaking the tracker to make it seem like I walked way more than I actually did, it was just a force of habit that I couldn’t seem to control. But with the technology we have in our phones, we can track more than just our steps in a day, but for the week,the month and the year. It also tracks the amount of miles we walked and how many flights of stairs we have climbed throughout the day. This may seem like small details but they are surprising when you actually take a look and find out information that you weren’t even expecting.

According to the app, I took an average of 11,166 steps in the week of Nov 7-13. I average almost the same amount of steps this week as I did last week, so far this month I’m averaging fewer steps than I did last month by around 650 steps per day and I’m already averaging more steps per day this year than I did last year. Collecting this data was actually very fun and easy, I learned a lot of new things that I didn’t even know. It was so easy to track and access this data that I will still continue to keep track of the data to see if there are any big changes in my routine.

Bridget’s Mini-Project Data Collection: Time Spent on Instagram

I made my project about how much time I spend on Instagram daily. I’m normally on my phone during my free time; when it comes to riding the train, walking home, going to school, getting out of awkward situations, or just when I’m bored. I always feel like I stay on my phone for hours just looking and browsing memes. I know I’ve been on my phone for way too long when I keep refreshing the page to see new posts and the same things that I saw come up. I got Instagram when I was in 8th grade (5-6 years ago). It was the newest popular thing but it wasn’t really as appealing due to people mainly using it to post pictures/videos. I started getting more into it when Vine came out and people started posting their funny content on Instagram. Instagram has widened worldwide and is used for so many different things (advertising, selling, becoming an “influencer”, posting funny content/memes, a safe space for some, posting about your opinions about things you care about or don’t care about). It has a wide variety of things to look at and adjusts to your preferences by collecting data about your activity over the years; it’s hard not to get hooked on for hours.

Based on my week’s worth of data collection, I found out that I spend about 5 hours and 24 minutes on Instagram on average daily. On my average weekday, I spent 1 hour on Instagram on the train on my way to school. In school, I spent, on average, 24 minutes on my phone since I only have 2 classes on average each day. I spent 1 hour of my time on Instagram on the way back home. I spent about 2 hours on Instagram at home since I didn’t really have anything to do. I go to work and I usually don’t use my phone the whole time because I like listening to music on my way there and I’m not allowed to use my phone while I’m working. I also listen to music on my way home just to chill and relax after a stressful workday. Once I get home, I spend about an hour on Instagram just so I can procrastinate on doing homework. I figured out that I mostly use Instagram when I’m bored or I have nothing to do; it’s just a distraction. 

I believe that if I showed my data to someone else, they would think that I don’t do much. Almost five hours and a half on Instagram are so much time wasted, I would understand their judgment completely because it’s somewhat true. Like I do stay busy but sometimes you just wanna laugh or not be bored and bring some excitement into your life. They must also think that I enjoy being on social media a lot since I waste a lot of my time on it. If I saw that, I would think that I was one of those people who are constantly on Instagram trying to get the most likes, or someone trying too hard to become an “influencer”. I’m personally not like that, I just go there to laugh, see stupid things, and get informed about stuff here and there. 

After analyzing my data, I figured out that I spend too much time on Instagram. It made me realize that I should cut down on how much time I spend on my phone/Instagram because most of the time its to get out of doing homework and/or distracting myself. I could put that time to better usage, such as, completing homework ahead of time, studying, and running errands. If I cut down on my phone usage, 80% of my problems would probably be solved. I enjoyed this project because it made me more self-aware of what I do the most and how I spend my time.

Olivia’s “Our Data” Reflection

We ended up talking about Facebook and its categories in my evening graduate seminar too, so I looked at my own Facebook data, and thought I should do the same reflection assignment that I asked you to do.

What did I find?

Some stuff that was not surprising: Facebook’s top category for me is “away from hometown,” they know I work in education, they know I’m a government employee, they know I’m a frequent traveler, they know I use Facebook on mobile a lot but also on wifi, they know I’m a commuter. (That means they notice I access Facebook in regular location-based patterns on weekdays!) They know my political views (ish)

The thing that was most surprising: One of the categories they have me in is “Friends of Soccer Fans.” There’s a whole advertising category just for people who are “top 2 friends” of people who display a deep interest in soccer. Why is that even a category??? Two of my cousins are big into soccer, and neither uses Facebook very much, so I assume it’s one of them. Also they know what model phone I have and that I fairly recently changed mobile networks. Also “birthday in October” is one of their ad categories– I’m not sure what they would advertise to me differently based on that.

What is accurate, what is not accurate? Everything was accurate except perhaps two things. There is a category called “Multicultural Affinity: African American.” If that means they think I’m Black, they’re wrong, but if they just think I display an above-average interest in African American issues, I suppose that’s probably true, I do try to be aware.
They also marked me as Top 5% and Top 10% of richest zipcodes, which is wrong. I am far away from the top 5 or 10% of richest people, but I Googled which zipcodes are the richest, and it seems that I’m in these categories because they know I live in New York, but their algorithms don’t know where I live, just where I spend a lot of my time (in midtown! Which is pretty rich!)

What changes to my privacy settings? None to my privacy settings, but I am going to remove more of my “liked” pages that I liked when I was like 13 and wanted to Like every page.

I think what I think the advantages and disadvantages are about this should be pretty clear to you by now.

Class 11/11

Finding Your Data

Click on the links below for directions on how to view your data on each site.

Google: https://www.teenvogue.com/story/all-the-data-google-has-on-you

Google ads specifically: https://gizmodo.com/find-out-what-google-thinks-you-want-to-see-in-ads-and-1677941497

Facebook: https://www.facebook.com/help/1701730696756992?helpref=hc_global_nav

Facebook ad preferences specifically: https://www.facebook.com/help/247395082112892

Instagram: https://help.instagram.com/181231772500920

Apple: https://www.cnet.com/how-to/find-out-what-data-apple-has-on-you/

If you have another site you want to look at, let me know and I can find directions for you!

Analyzing Your Data

During class or after class for homework, write up answers to the following questions (and email them to me or post them to the blog):

  1. What did you find about yourself? 
  2. What surprised you?
  3. What was accurate, and what was not accurate?
  4. What changes do you want to make to your privacy settings, if any?
  5. What are the advantages and disadvantages of websites keeping this data on you?

 

Targeted Ads in Real Life

What a coincidence! When I got home today, after our discussion on targeted advertising in the mail, I checked my own mail and found an Amazon gift catalog addressed to my partner (pictured below). Because the intended audience seems to clearly be couples, I wondered if this was a targeted ad, and if there were other catalogs that other kinds of people were receiving. (PLEASE post a comment if you get one in your mail and tell us how it is different!!)

Magazine cover featuring a white heterosexual couple posing in winter clothes. Text reads “Holiday Together: 2019 Gift Guide. Fashion” with an Amazon logo beneath

I looked up Amazon holiday catalogs online, and all of the top search results were about their Holiday Toys catalog(s) and how they are probably sent to customers who buy “back to school” items on their Amazon accounts, because that’s a reliable indicator of having children, and therefore of buying toys for Christmas. So definitely there are other ones, which means this one was specifically for us!

Here is how I know this catalog is targeted toward us:

There are clearly other holiday gift catalogs that Amazon is sending out, but we got the “adult couples with no children” catalog as opposed to the “children live in your home” catalog. We also use the same Amazon account because we only have one Prime membership, so it makes sense that they noticed that there are two kinds of purchasing profiles mixed together in our buying history, plus our saved addresses are two different names for the same address. So, a couple.

But we also got the fashion-specific one. Most of our purchases on amazon are my books for graduate school and individual clothing items for specific events (like the several weddings we’ve been to in the last year and Halloween). So, the algorithm decides we are interested in fashion and that is the category of purchase we are most likely to make. (Where is my academic book catalog though??? Probably they know I only buy a lot of books twice a year, at the start of each semester.)

There are also a lot of ads for sweaters, hats, and jackets—I bet people who live in warmer climates get different ones.

There’s a couple ads for baby clothes, but I’m not sure what’s up with that—we are definitely not having a baby. Maybe it’s not that hyper specific and they figured adult couples sometimes have kids, but we didn’t score high enough on the “probably have kids” scale to get the toys one.

 

 

Data Collection Mini-Project

Due November 13 (Wednesday) by the end of the day

For this project, you will spend a week or two collecting data about your own life, analyze the data, and then write about your findings.

This is a small-scale, analog version of the kinds of data analytics that companies (Facebook, Amazon, Google, etc) conduct on our data all the time. The purpose is to get you thinking about all of the information that can be gleaned about your life all the time, and what inferences can be made about it.

Directions:

1. Choose what data you want to collect about yourself. It can be something your phone collects automatically (steps per day, app usage via the ScreenTime feature or something similar), or something you notice and write down yourself (like which subway stops you use at approximately which times). It can be anything that is 1) manageable for the scope of the assignment and 2) something you think will be interesting to learn from.

2. Collect/track/save that data for a week or two. Make sure that your dataset is complete (for example, if you’re tracking your subway usage, write down every single time you write the train and don’t miss any).

3. Analyze your data. Think about what it says about you. If you showed someone your data without telling them anything else about you, what assumptions would they make? What are some good educated guesses that could be made about you based on your data (even if these guesses are not accurate). Why?

It may be useful to actually show your data to someone else and ask them what they assume/conclude and why.

4. Write 2 or more pages about your experience, explaining what you chose for your project, a summary of your data, and your analysis.

5. Post your writing to the blog and tag it “Data Collection” and tag it with your name. (You may choose whatever privacy setting you want)

6. Respond to at least two of your classmates with your reactions/observations/thoughts about what they discovered