Dylan Giuliano

Research Portfolio

Two Years on the Same Question

Both papers examine how digital platforms shape consumer behavior. The first focused on the data infrastructure — how platforms harvest behavior and sell it to advertisers. The second asked why those ads actually work, tracing it to the psychology of parasocial relationships and the trust they manufacture.

2025–2026 · Atholton High School

The Friend You've Never Met: The Psychology of Parasocial Marketing

A qualitative meta-analysis of three peer-reviewed studies on how parasocial bonds between audiences and digital personalities influence consumer trust, brand loyalty, and purchasing behavior. The paper also addresses AI-generated influencers and the ethical implications of engineered parasocial attachment.

Research question: How do parasocial relationships between consumers and digital personalities influence trust, brand loyalty, and purchasing decisions — and what are the psychological effects on consumers?

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Key Findings

  • Stronger parasocial bonds consistently predict higher trust and purchase intent across all three reviewed studies (Chung & Cho 2017, Balaban et al. 2022, Lim et al. 2025).
  • Authenticity is the load-bearing variable: overcommercialization erodes parasocial bonds, while transparent sponsorship disclosure tends to preserve them.
  • Follower count is a poor proxy for marketing impact. What matters is bond depth — specifically whether a follower has reached identity-level integration with the creator.
  • AI-generated influencers can produce meaningful parasocial bonds comparable to human creators, raising ethical questions the industry has not seriously addressed.
  • Adolescents are the most susceptible group. The ethical literature on this is critically underdeveloped.

Methodology: Qualitative meta-analysis. Includes a personal interview with Dr. Cynthia Hoffner (March 2026).

2024–2025 · Atholton High School

Profiled and Targeted: The Data Economy Behind Social Media Algorithms

An examination of how platforms like Meta, Google, and TikTok collect behavioral data, convert it into consumer profiles, and monetize those profiles through real-time ad auctions. The paper evaluates the tradeoff between advertising efficiency and the ethical risks to privacy, autonomy, and consent under limited U.S. regulation.

Research question: How do social media algorithms monetize user attention, and what are the ethical implications of that system for consumers?

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Key Findings

  • Algorithms function as attention engines: engagement data is the raw material for ad targeting.
  • Behavioral profiles are built in real-time and sold in millisecond ad auctions consumers never see.
  • Small business benefits from targeted advertising do not offset the systemic risks of large-scale behavioral surveillance.
  • U.S. regulatory frameworks significantly lag behind platform capabilities.

Methodology: Qualitative synthesis of peer-reviewed journals and federal reports. Includes an interview with Jessica Lang of Prof G Media.

Timeline: September 2024 – May 2025. Included a class presentation (December 2024) and a tri-fold library display (March 2025).