Surface Level
To a person behind the screen at a company coding algorithms, to the massive computers filled with user data, and to advertisers paying to push their products onto social media platforms, I am nothing more than what information they can gather from me and what I reveal about myself online. This is the information that gets collected, stored, and used to create a computer-based model for me that can predict my behaviors and my personality more accurately than humans can (Youyou et al. 2015). As an avid social media user, especially Instagram, it is absolutely certain that with the eight hours I spend on that app per week, my computer-based model becomes more accurate and nuanced to who I am as a person. But how much of me do they know?
I have three Instagram accounts, each account catering towards a different group of people. My main Instagram account is what I want people to see about myself–my followers include high school friends, college friends, and acquaintances. I have a spam account for my close friends where I “photodump” my silly photos or repost funny posts that I see on my feed. And finally, I have an art account where I post my drawings under an online alias. Together, these three online identities contribute to my computer-based model, about who I am to these companies, brands, and developers.
In signing up for my Instagram accounts, I provided basic information about myself to the app. My name is Alicia Zhang, my birthday is February 2nd, 2003. That makes me nineteen years old. Through the people I follow and tagged photos on my main account, they know that I lived in Neenah, Wisconsin my whole life, and attended Neenah High School. Through my own posts with tagged locations, the app also knows that I live in the Bay Area in California, and one glance at my bio shows that I am a student at UC Berkeley, graduating in 2025. Living in the Midwest, I primarily grew up with caucasians–an immediate look at my profile picture shows that I’m chinese. Taking a glance at the list of people I follow, the algorithms can deduce even more information about me. Besides my friends and acquaintances, I follow influencers, my favorite bands and singers, actresses, artists, as well as science and Christian pages. My hobbies include art of all kinds: digital art, painting, embroidery, and music (Appendix Fig. 1). Recently I have been interested in ‘broken humor’ posts, skincare, and jewelry.
The Instagram “explore” tab is how the app targets me as a user to show me content they think I would enjoy. In a video made by Adam Mosseri, the head of Instagram, he explains that the algorithm looks at information about a certain post and your interactions with the poster, your activity, and the content you interact with. The algorithm then creates a guess on your interest levels based on how likely you are to interact with the post. Then, the app arranges your explore feed (Adam Mosseri). Across all three of my accounts, my explore page matches with the type of content I interact most with on each account. My main account’s explore page shows various Christianity posts, viral reels from Asian creators, musicians I enjoy, artwork, and a variety of funny posts. On my spam account, I save posts about earrings and skincare and follow humor accounts, so my explore page is entirely filled with photos of earrings, milky skincare routines, and reposts of reddit posts and tweets. And for my art account: arts and craft content (Appendix Fig. 2). Even the Instagram shop tabs across all accounts are curated to my account’s interests, from jewelry to clothing to sticker art. These examples all demonstrate who I am to an algorithm and as a user of a platform.
While an algorithm is capable of predicting my interests, they cannot pick up on the subtleties of myself and the deeper things I value. These parts of me are not aspects that can be marketed to, and have so much more meaning and impact to me than the surface-level demographics that they see daily. I am Alicia Zhang–a student, scientist, musician, artist. Biology has always been something that I deeply enjoy, especially biomedical research and the impact that I could make on the lives of those who are sick. Within the scope of this class, I want to research the political and socioeconomic impacts of the polio epidemic and the polio vaccine. I believe that prevention as well as seeking treatments and cures for diseases is vital to saving lives, but I also want to learn more about the effects that diseases can have beyond an individual life to maximize my understanding of the most effective way to develop and implement a widespread treatment. Besides science, it’s the little things that make me happy: the sun coming out after a cloudy morning, seeing stray cats on the street, when my Spotify shuffle plays my favorite songs back-to-back. In a crowd of my favorite people, I’m one of the loudest, but I am an introvert and a homebody, meaning meeting new people is always difficult for me since I dislike small talk. It’s difficult to get to know me on a very personal level, for although I am friendly, I am a closed book.
Beneath my composed appearance are the deep thoughts and experiences that shape me to be who I am. I value achievement, belonging, dependability, efficiency, and happiness. Being surrounded by people who accept me and whom I can depend on is what contributes to my happiness the most. And my value for success comes packaged with my enneagram–a three. While my strive for excellence has certainly paid off in terms of receiving recognition, the trade-off is the immense pressure I put on myself (Appendix Fig. 3). Since middle school, I worked hard to achieve good grades and now that I’m in college, that pressure to do well has evolved into a fear of failure, but I also have changed to be mentally well-prepared to handle that pressure as well. Because I’m not an emotional person and do not get overwhelmed easily, it allows me to think clearly and logically about my problems so that I can find a solution or adapt to the issue. Not every decision gets made with clear logic of course, thanks to my cognitive biases. In the list of cognitive biases that neuropsychiatrist Dilip V. Jeste includes in his article “Wiser”, the ones I relate most to are loss aversion and escalation of commitment, both of which play into my value of efficiency. Loss aversion is when you perceive loss as more severe than gains, and escalation commitment is the tendency to stick with a decision because you have already put too much work into something (Jeste 2020). In order to make the most of my time, I try to avoid failure as much as I can, since that means I have to start over and try again. Likewise, and sometimes contradictory to loss aversion, if I have invested time into a project, even if it may be on its way to failure, I continue working and attempt to ‘save’ the project because it feels too late to start over.
Aside from struggles connected to schoolwork or decision-making, I also wrestled with my identity as a Chinese American. According to the US 2020 Census for Wisconsin, Asians make up 6% of the population, while the percentage of white people is 61.6% (America Counts Staff 2021). Within my county, Winnebago county, the percentage of Asians drops even further to 3.3%, and the percentage of white people increases to 86.2% (Appendix Fig. 4). Because I grew up with all my white peers at school, I felt ashamed to be Chinese. I was embarrassed by my last name, my mom’s heavy Chinese accent, and the leftovers I brought to school for cold lunch. Even though I grew up also attending a Chinese church with other Chinese kids, I felt like I was one with the white kids at school–American Chinese, not Chinese American (Appendix Fig. 5). It was not until high school when I made friends that were proud to be asian, that I finally began to embrace this integral part of my identity.
Something that I discovered as I unravel these two parts of myself–what algorithms see versus what I see–is that targeted products and social media are more geared, at least from my experience, towards things and items that I’m interested in, which more or less are not affected by my demographic. The products and posts I see on social media are affected by who I follow and what content I interact with, but it is really easy to change what content I see, especially on Instagram. My interests change fairly rapidly, and as such, my Instagram explore has shifted to match those interests. Between my phases of obsession with bullet-journaling, video games, nail art, and friendship bracelets, my explore page at each interest looks like it could belong to somebody else. I find that even though Instagram has tracked all my basic information, especially location, race, beliefs, etc, the only targeted content I see is based on what I interact with the most and the accounts I follow, which typically just reflects my interests at the time. Aspects of myself that are more nuanced, complex, and hidden are unable to be targeted. This simply demonstrates how easy it is to mislead the algorithm, and is a reminder that even though technology and machine learning are becoming more advanced, we can still outsmart them. While computers are on track to being much smarter than any human, what still sets us apart from them are the emotions we feel and the things we experience, which a computer cannot relate to and thus cannot incorporate our feelings into their algorithm of products. So while Instagram will continue recommending me posts about ear piercings and whatever else interests me at the moment, I am content with knowing that the abstract aspects of myself that deeply shape me will not appear on my screen as an Instagram post.
I have three Instagram accounts, each account catering towards a different group of people. My main Instagram account is what I want people to see about myself–my followers include high school friends, college friends, and acquaintances. I have a spam account for my close friends where I “photodump” my silly photos or repost funny posts that I see on my feed. And finally, I have an art account where I post my drawings under an online alias. Together, these three online identities contribute to my computer-based model, about who I am to these companies, brands, and developers.
In signing up for my Instagram accounts, I provided basic information about myself to the app. My name is Alicia Zhang, my birthday is February 2nd, 2003. That makes me nineteen years old. Through the people I follow and tagged photos on my main account, they know that I lived in Neenah, Wisconsin my whole life, and attended Neenah High School. Through my own posts with tagged locations, the app also knows that I live in the Bay Area in California, and one glance at my bio shows that I am a student at UC Berkeley, graduating in 2025. Living in the Midwest, I primarily grew up with caucasians–an immediate look at my profile picture shows that I’m chinese. Taking a glance at the list of people I follow, the algorithms can deduce even more information about me. Besides my friends and acquaintances, I follow influencers, my favorite bands and singers, actresses, artists, as well as science and Christian pages. My hobbies include art of all kinds: digital art, painting, embroidery, and music (Appendix Fig. 1). Recently I have been interested in ‘broken humor’ posts, skincare, and jewelry.
The Instagram “explore” tab is how the app targets me as a user to show me content they think I would enjoy. In a video made by Adam Mosseri, the head of Instagram, he explains that the algorithm looks at information about a certain post and your interactions with the poster, your activity, and the content you interact with. The algorithm then creates a guess on your interest levels based on how likely you are to interact with the post. Then, the app arranges your explore feed (Adam Mosseri). Across all three of my accounts, my explore page matches with the type of content I interact most with on each account. My main account’s explore page shows various Christianity posts, viral reels from Asian creators, musicians I enjoy, artwork, and a variety of funny posts. On my spam account, I save posts about earrings and skincare and follow humor accounts, so my explore page is entirely filled with photos of earrings, milky skincare routines, and reposts of reddit posts and tweets. And for my art account: arts and craft content (Appendix Fig. 2). Even the Instagram shop tabs across all accounts are curated to my account’s interests, from jewelry to clothing to sticker art. These examples all demonstrate who I am to an algorithm and as a user of a platform.
While an algorithm is capable of predicting my interests, they cannot pick up on the subtleties of myself and the deeper things I value. These parts of me are not aspects that can be marketed to, and have so much more meaning and impact to me than the surface-level demographics that they see daily. I am Alicia Zhang–a student, scientist, musician, artist. Biology has always been something that I deeply enjoy, especially biomedical research and the impact that I could make on the lives of those who are sick. Within the scope of this class, I want to research the political and socioeconomic impacts of the polio epidemic and the polio vaccine. I believe that prevention as well as seeking treatments and cures for diseases is vital to saving lives, but I also want to learn more about the effects that diseases can have beyond an individual life to maximize my understanding of the most effective way to develop and implement a widespread treatment. Besides science, it’s the little things that make me happy: the sun coming out after a cloudy morning, seeing stray cats on the street, when my Spotify shuffle plays my favorite songs back-to-back. In a crowd of my favorite people, I’m one of the loudest, but I am an introvert and a homebody, meaning meeting new people is always difficult for me since I dislike small talk. It’s difficult to get to know me on a very personal level, for although I am friendly, I am a closed book.
Beneath my composed appearance are the deep thoughts and experiences that shape me to be who I am. I value achievement, belonging, dependability, efficiency, and happiness. Being surrounded by people who accept me and whom I can depend on is what contributes to my happiness the most. And my value for success comes packaged with my enneagram–a three. While my strive for excellence has certainly paid off in terms of receiving recognition, the trade-off is the immense pressure I put on myself (Appendix Fig. 3). Since middle school, I worked hard to achieve good grades and now that I’m in college, that pressure to do well has evolved into a fear of failure, but I also have changed to be mentally well-prepared to handle that pressure as well. Because I’m not an emotional person and do not get overwhelmed easily, it allows me to think clearly and logically about my problems so that I can find a solution or adapt to the issue. Not every decision gets made with clear logic of course, thanks to my cognitive biases. In the list of cognitive biases that neuropsychiatrist Dilip V. Jeste includes in his article “Wiser”, the ones I relate most to are loss aversion and escalation of commitment, both of which play into my value of efficiency. Loss aversion is when you perceive loss as more severe than gains, and escalation commitment is the tendency to stick with a decision because you have already put too much work into something (Jeste 2020). In order to make the most of my time, I try to avoid failure as much as I can, since that means I have to start over and try again. Likewise, and sometimes contradictory to loss aversion, if I have invested time into a project, even if it may be on its way to failure, I continue working and attempt to ‘save’ the project because it feels too late to start over.
Aside from struggles connected to schoolwork or decision-making, I also wrestled with my identity as a Chinese American. According to the US 2020 Census for Wisconsin, Asians make up 6% of the population, while the percentage of white people is 61.6% (America Counts Staff 2021). Within my county, Winnebago county, the percentage of Asians drops even further to 3.3%, and the percentage of white people increases to 86.2% (Appendix Fig. 4). Because I grew up with all my white peers at school, I felt ashamed to be Chinese. I was embarrassed by my last name, my mom’s heavy Chinese accent, and the leftovers I brought to school for cold lunch. Even though I grew up also attending a Chinese church with other Chinese kids, I felt like I was one with the white kids at school–American Chinese, not Chinese American (Appendix Fig. 5). It was not until high school when I made friends that were proud to be asian, that I finally began to embrace this integral part of my identity.
Something that I discovered as I unravel these two parts of myself–what algorithms see versus what I see–is that targeted products and social media are more geared, at least from my experience, towards things and items that I’m interested in, which more or less are not affected by my demographic. The products and posts I see on social media are affected by who I follow and what content I interact with, but it is really easy to change what content I see, especially on Instagram. My interests change fairly rapidly, and as such, my Instagram explore has shifted to match those interests. Between my phases of obsession with bullet-journaling, video games, nail art, and friendship bracelets, my explore page at each interest looks like it could belong to somebody else. I find that even though Instagram has tracked all my basic information, especially location, race, beliefs, etc, the only targeted content I see is based on what I interact with the most and the accounts I follow, which typically just reflects my interests at the time. Aspects of myself that are more nuanced, complex, and hidden are unable to be targeted. This simply demonstrates how easy it is to mislead the algorithm, and is a reminder that even though technology and machine learning are becoming more advanced, we can still outsmart them. While computers are on track to being much smarter than any human, what still sets us apart from them are the emotions we feel and the things we experience, which a computer cannot relate to and thus cannot incorporate our feelings into their algorithm of products. So while Instagram will continue recommending me posts about ear piercings and whatever else interests me at the moment, I am content with knowing that the abstract aspects of myself that deeply shape me will not appear on my screen as an Instagram post.
Appendix
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Works Cited
Adam Mosseri [@mosseri]. How the “Algorithm” Works. Instagram, 23 Jun. 2021, https://www.instagram.com/p/CQdxvdNJ_sC/?utm_source=ig_embed&utm_campaign=embed_video_watch_again
America Counts Staff. "Wisconsin Population Increased 3.6% Since 2010." https://www.census.gov/library/, 25 Aug. 2021, www.census.gov/library/stories/state-by-state/wisconsin-population-change-between-census-decade.html#:~:text=Race%20and%20ethnicity%20(White%20alone,or%20More%20Races%2010.2%25).
Jeste, [Excerpts on] Cognitive Biases in Wiser, 2020
Neenah Joint School District. "Back to School." Dialogue, [Neenah], 2020.
Youyou, Wu, and Michal Kosinski. "Computer-based personality judgments are more accurate than those made by humans." Psychological and Cognitive Sciences, vol. 112, no. 4, 12 Jan. 2015, PNAS. www.pnas.org/doi/full/10.1073/pnas.1418680112.
Zhang, Alicia. “Instagram Explore Page.” Screenshot, 20 Sept. 2022.
Zhang, Alicia. Various photographs.
America Counts Staff. "Wisconsin Population Increased 3.6% Since 2010." https://www.census.gov/library/, 25 Aug. 2021, www.census.gov/library/stories/state-by-state/wisconsin-population-change-between-census-decade.html#:~:text=Race%20and%20ethnicity%20(White%20alone,or%20More%20Races%2010.2%25).
Jeste, [Excerpts on] Cognitive Biases in Wiser, 2020
Neenah Joint School District. "Back to School." Dialogue, [Neenah], 2020.
Youyou, Wu, and Michal Kosinski. "Computer-based personality judgments are more accurate than those made by humans." Psychological and Cognitive Sciences, vol. 112, no. 4, 12 Jan. 2015, PNAS. www.pnas.org/doi/full/10.1073/pnas.1418680112.
Zhang, Alicia. “Instagram Explore Page.” Screenshot, 20 Sept. 2022.
Zhang, Alicia. Various photographs.
Reverse Outline
- My research paper explores aspects of myself from my own perspective as well as the marketing/algorithmic side. I talk about my online activity mainly on Instagram, and how through my 3 instagram accounts and the content I interact with, I see how the app is targeting me as a user through the Instagram explore page. I also discuss how the algorithm only targets surface-level interactions and doesn’t show me content based on parts of myself that are deeper and more nuanced.
- The claims I make about the algorithm only pushing content that I interact with has purely been based off of my own experiences and from what I notice and track when I use Instagram. This could be different for somebody else, or somebody could argue that the algorithm is able to target more complex parts of my personality, which goes against what I claim.
- The complexity of this topic is that everyone’s social media experience is different. Ever since the aim for companies to create a more ‘customized’ experience for their users, no person’s feed is the same as another’s, which adds layers to claims such as the ones I am making.
- Conceptual Questions:
- What information from a person does an algorithm really use when pushing customized content on social media?
- To what extent can algorithms use information about ourselves to know who we really are?
- How does who we are as a person change the way we use the internet?
- Claims:
- P1: I am nothing more than what information they can gather from me and what I reveal about myself online
- P2: Together, these three online identities contribute to my computer-based model, about who I am to these companies, brands, and developers.
- P3: In signing up for my Instagram accounts, I provided .basic information about myself to the app.
- P4: The Instagram “explore” tab is how the app targets me as a user to show me content they think I would enjoy.
- P5: While an algorithm is capable of predicting my interests, they cannot pick up on the subtleties of myself and the deeper things I value. These parts of me are not aspects that can be marketed to, and have so much more meaning and impact to me than the surface-level demographics that they see daily.
- P6: Beneath my composed appearance are the deep thoughts and experiences that shape me to be who I am.
- P7: Aside from struggles connected to schoolwork or decision-making, I also wrestled with my identity as a Chinese American.
- P8: I find that even though Instagram has tracked all my basic information, especially location, race, beliefs, etc, the only targeted content I see is based on what I interact with the most and the accounts I follow, which typically just reflects my interests at the time. Aspects of myself that are more nuanced, complex, and hidden are unable to be targeted.
- Repetition and Skepticism: While I don’t think I’m necessarily repeating my terms or ideas, I find that for phrases or concepts that I use throughout my paper, I say them the same way each time without that much variation, which could get boring for my reader.
- Evidence: Overall I think the evidence I’ve used is pretty solid, but I want to find some solid evidence to back up my claim in paragraph 8 that I stated above for question 5. That would really solidify my argument.
- Structure: I am very satisfied with my structure, but I am considering splitting my last paragraph into two parts so I have a formal conclusion.
- Deepening: what’s missing that needs to be added?
- I want to add some better transitions between a few of my paragraphs to make the ideas connect to each other better, and I also need to simplify some things that I’m saying so I can cut down on words. Based on the feedback left by my classmates, I also could expand on a few of the things that I say.
Reverse Outline:
- Intro Paragraph
- Information collected by companies about online activity
- EVIDENCE: computer-based model
- Transition: but how much of me do they know?
- Paragraph 1
- My online activity
- Three instagram accounts
- Paragraph 2
- Information that Instagram sees about me
- Name, age, hometown, education, demographics
- Who I interact with online
- Hobbies
- MULTIMODAL EVIDENCE: painting
- Paragraph 3
- Instagram algorithm
- EVIDENCE: how the algorithm works
- My explore pages on my instagram accounts
- MULTIMODAL EVIDENCE: screenshot of my explore page
- Paragraph 4:
- Transition: algorithm cannot pick up on the subtleties of myself and the deeper things I value
- Biology and research within this class
- What makes me happy
- Personality
- Paragraph 5
- Values that shape me
- Pressure to do well
- MULTIMODAL EVIDENCE: school news snippet
- Logical thinking
- Cognitive biases
- Paragraph 6
- Identity as a Chinese American
- EVIDENCE: Statistics about Wisconsin
- MULTIMODAL EVIDENCE: graph of statistics about Wisconsin
- Feelings of shame
- MULTIMODAL EVIDENCE: fifth grade class photo
- Paragraph 7
- Algorithms see vs I see
- Not really affected by demographic, but who I interact with
- Easy to change what I see
- Changing interests
- Nuanced parts of myself aren’t targeted because technology isn’t advanced enough to do that
- Sets us apart from computers