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

Halloween Extra Credit: Olivia Wood

Olivia wearing a black wig and no glasses with purple cat ears and a rainbow unicorn horn

I thought it would be best if I lived up to my own assignment this time! This Halloween, I dressed up as my friend Maddie because she already owns the goth aesthetic I aspire to every Halloween, and it was a low-effort Halloween costume while still being creative and not a cop-out idea. Maddie loves cats, unicorns, stickers, and sparkles, and she is a professional poet, so I’m wearing cat ears with a rainbow unicorn horn, painted my nails sparkly, and I have stickers and silly Halloween poems that I wrote to hand out to people. Maddie is a great person, a great writer and artist, and a great friend, so she is definitely someone I aspire to be more like.

Garnet from Steven Universe in her wedding outfitMy original idea for Halloween was to be Garnet from Steven Universe in her wedding outfit. I love Steven Universe for its wholesome, loving themes, queer representation, and abundance of  kickass women. And aliens! I relate to Pearl the most personally, but I love how Garnet’s outfit combines both a suit and a dress (masculine and feminine dress). I alternate between whether I like suits or dresses best depending on the day, so seeing Garnet combine both made me happy.

Note: You don’t have to write as much as I did, but you’re welcome to!