This research explores how social media algorithms are engineered to maximize user engagement by harvesting data and creating ultra-targeted advertising ecosystems. The goal: monetize attention by turning user behavior into a usable consumer profile that advertisers harness to target their customers.
Abstract Social media's rapid growth over the last decade has enabled tech giants like Google, Meta (Facebook), and TikTok to collect a massive amount of user data, driving their collective market capitalization into the trillions of dollars. These companies monetize their “free” platforms through highly targeted advertising, powered by algorithms that analyze user data to create detailed consumer profiles. While this innovation allows advertisers, especially small businesses, to efficiently reach their ideal audiences, it raises ethical concerns about privacy, data collection practices, and the virtually unchecked power of these corporations. Research shows a lack of stringent regulations in the U.S., enabling these companies to operate with limited oversight, posing potential risks to citizen privacy and autonomy. As individualized marketing continues to grow, it is essential to understand how it works, the benefits, and drawbacks to ensure responsible and fair use of this revolutionary technology.
This paper was built using a qualitative synthesis of peer-reviewed journals, federal reports, and a professional interview. I focused on three core themes: algorithmic behavior, data monetization, and platform ethics.
I used advanced search queries to source credible literature—such as FTC publications and academic marketing analysis—and cross-referenced each for accuracy and relevance. The interview with Jessica Lang of Prof G Media brought a real-world business lens to the findings, especially regarding the impact on small businesses.
Though the research was limited by lack of transparency from tech companies, every source was dissected to extract its implications on privacy, engagement loops, and user profiling.
If you’re looking for a deeper breakdown, download the full research paper below.
Download PDFTopic exploration and selection.
Research questions, hypothesis, source note taking.
Reading existing literature.
Presented to another class about what research I have so far. Continued reading literature. View Slides (PDF)
Located research gaps about how data is used for algorithms. Conducted an interview with Jessica Lang from Prof G Media. Created and submitted research proposals. Began primary research.
Month dedicated to primary research. Conducted a qualitative literature synthesis of different scholarly journals on social media algorithms to identify commonalities between platforms.
Created outline for research paper. Built a tri-fold display board (pictured) for the school library.
Writing final synthesis paper.
Research paper polished and published.
Digital portfolio website created to display research.