Maggie O'Meara

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It is probable to expect that every person I encounter has a different perspective of me. These people will have good and bad memories of me, forming their own idea of who I am. A stranger on the subway sees me as the girl who rushed onto the last cable car to make the 7am commute. My classmate thinks of me as the girl who could spit out mental math like a calculator. However, when one first reads the name, Maggie O’Meara, an accurate depiction cannot be generated in their mind. How can one fully encompass the qualities of another based solely on their name? Yet, in our digital society names heavily define our various accounts, all while giving us voices within platforms. After searching my name, the only correct result I found is the public persona, @mags_omeara on Instagram. Of course other Maggie O'Meara's exist in this world, but 5 others share the same username as me; however their identities are masked behind the privatized security feature that these applications enable. These accounts were only found after further searching the username, as opposed to my name. While maintaining five different accounts, I noticed that my data identity changes depending on the social media platform, creating different digital figures that differ as I age. These personas alter the perception that both the data collector and other users have of me, subjectively skewing Big Data algorithms.

My Data Identities

@mags_omeara on Twitter, 2015

Current Presence

Although these other profiles are privatized, I am aware that Twitter, Snapchat, Facebook, Vsco, and LinkedIn still collect my data, forming multiple datasets, all independent of one another.

On Instagram, @mags_omeara attends the University of Michigan where she enjoys traveling, concerts, and cooking. When I go through all 269 posts, I could name over 20 of her close friends and family. Instagram @mags_omeara is lively.

On Twitter, she hasn’t posted in two years, but after looking at her likes, she enjoys memes, iCarly, jokes, and roasts. Twitter @mags_omeara is playful.

Snapchat @mags_omeara’s 24-hour posts are of yummy meals, focusing on lots of healthier desserts. Snapchat @mags_omeara is a chef.

On Facebook, her family tree seems to never end. She seems to be tagged in many posts from her mom, aunts, uncles, and cousins. Facebook @mags_omeara is family-oriented.

Looking on Vsco, @mags_omeara posts collages of her life. These consist of travel photos, edgy selfies, and film cameras. Vsco @mags_omeara is artsy.

Lastly, Linkedin consists of @mags_omeara’s accomplishments. She studies actuarial science and has passed 4 actuarial exams. She sits on the board of two student organizations and plans to move to Chicago for a full-time job upon graduation. LinkedIn @mags_omeara is successful.

Evolution of Identities

Further delving into each of these applications, you will find that the social media identity behind @mags_omeara has changed over the years, reflecting my personal growth.

I have been active on Instagram, Facebook, Twitter, and Snapchat since the beginning of high school. As I am experiencing different phases of life, my relationship with social media is also changing. In the beginning, I was obsessed with the engagement. Immature 14-year-old Maggie craved the affirmation of a heart-eyes emoji in the comments section of my posts from the popular girl in school. However, as I grew up, I realized that a face-to-face compliment is much more gratifying than a comment on my post. I was also active on Twitter, posting whatever I was doing, such as “prepared to eat my body weight tomorrow” on Thanksgiving Eve, 2015. Now, I would be considered a ghost user, one who scrolls, but doesn’t post and rarely engages in others’ posts. As an adult, I understand that the only people who need to know how much I eat on Thanksgiving are those who are sitting around my table.

While I’ve faded away from some of these platforms a great deal in recent years, I’m still fairly active on LinkedIn. This professional version of Maggie wasn’t born until I started college, due to the fact that I would now be entering the real-world in such a short time. LinkedIn is used to highlight academic achievements, while connecting with recruiters and employees within one’s preferred company and field. My engagement on this application has increased because my life is shifting from a social presence to a professional scene with college graduation dawning upon me.

Out of the six digital identities that make-up my digital footprint, each identity is a time-capsule reflecting both my past and present experiences and station in life, ultimately handing companies the data they need to create what my potential “real-life” personality is.

Data Policies

My Average Activity, Your Activity Page

After analyzing this evolution of my different digital identities, I arrived at the realization that my lack of posting on most platforms was a result of two major fears: recruiters seeing everything that encompasses my digital footprint, and companies taking advantage of user data. Both cases use algorithms to serve their purpose and both algorithms are unknown to the typical user - also known as the input data. Since results from Google are the only visible representations of the coy algorithms purposefully implemented by recruiters, I have become far-more intrigued in data privacy policies which social media platforms are legally obligated to display.

Every time a website or application is surfed, the user has agreed to its terms and conditions, creating a default opt-in system. If there is disagreement regarding the policy, there is no way to opt-out of data collection and continue to use the app. When a new user creates an account, the massive compilation begins. According to Instagram’s privacy policy, they collect all the user’s content, including the location of a photo shared, interactions with other users, hashtags, and more ( This forms a large web of data which further allows Instagram to form a profile that they assume similarly matches the users’ physical embodiment. When further exploring, I found the “Your Activity” page, which says that I average 50 minutes per day on Instagram. This adds up to 304 hours per year, and since I’ve been on the app for 7 years, that’s a total of over 89 days. While this is only a very small fraction of my entire life, 89 days creates a massive entanglement of data on the user: @mags_omeara. Instagram uses data to sell to advertisers and to give users recommendations for events, accounts to follow, and more, with the intention of keeping the user engaged and active in the app. After looking at the other applications’ data policies, they all conform to the same motto: the more we collect, the better.

Because the collection of data is specific to the content of that platform, using their large dataset to make in-app improvements is beneficial to the company. The issue arises when Big Data is sold to third parties. Although they will acquire massive data sets, it is biased due to the fact that it is incomplete. Crawford states that “A data set may have many millions of pieces of data, but this does not mean it is random or representative” (Crawford 8). When acquiring Instagram @mags_omeara, they will only get my lively side as opposed to only obtaining LinkedIn data, where they only see my professional side. For example, Cambridge Analytica obtained millions of users’ Facebook data to group people based on the OCEAN personality test in order to target them to vote a certain way politically (Resnick 1). If my Facebook data was sorted through this algorithm, @mags_omeara would score highly on agreeableness because I interact frequently with family, therefore assuming I have close family relationships. However, on Instagram, @mags_omeara would have a high score in extroversion, showing me a completely different targeted ad than on Facebook. Thus, the data that Cambridge Analytica and many other third parties receive is biased--they are not getting the full picture of their users’ digital footprint, nor their users’ physical identity. Overall, the dataset is not wholly representative of the individual, rather only indicative of the parts which the user chooses to broadcast on that platform. Even then, can one confidently assume that an accurate image of someone is based solely on their social media?


Just as the stranger on the subway sees me as the girl rushing to work, that interaction is only a fraction of my personal embodiment and cannot be used to create a complete understanding of my identity. While I am on six major platforms, each only contributes to 1/6 of my digital footprint, and an even smaller fraction of my whole identity. As a result of my constant evolution, the input data on me is exclusive to the specific phase of life, skewing Big Data sets. Whether companies use this data to make a profit from other big technological corporations, or use it to enhance their own applications, the data collected on each individual user is misrepresented due to its limited scope. Essentially, the user does not equal the person. If companies want to successfully use my data, they have to see me simply as a user and not an entire person within that user. Big tech only views @mags_omeara as lively, playful, a chef, family-oriented, artsy, and professional. But needless to say, I am much more.


Danah Boyd & Kate Crawford (2012) CRITICAL QUESTIONS FOR BIG DATA, Information, Communication & Society, 15:5, 662-679, DOI:10.1080/1369118X.2012.678878

Data Policy. (n.d.). Retrieved Februrary 18, 2021, from

Resnick, B. (2018, March 23). Cambridge Analytica's "psychographic microtargeting": What's bullshit and what's legit. Retrieved February 18, 2021, from