Video Presentation
Project Overview
Plot Points is my DIY API small data project exploring the cultural and commercial impact of BookTok. Using a dataset of 180 viral book titles from January–May 2025, I analyzed patterns in genres, diversity representation, adaptation trends, and emotional tropes that fuel TikTok-driven book sales. Data was collected from my own feed and three additional reader personas to explore how TikTok’s algorithm shapes different viral trends.
- Python (pandas, requests)
- Open Library API
- TMDB API
- Tableau Public
- Excel
- Canva
Key Questions
- What genres dominate BookTok’s viral lists?
- How do adaptation buzz, diversity representation, and tropes influence engagement?
- Do indie and self-published books thrive as much as traditionally published ones?
- How do reader identity and preferences change the algorithm’s recommendations?
Reader Personas
I created four distinct reader profiles to analyze how BookTok recommendations differ across identities, interests, and communities:
- Alex – Sci-fi thrillers & Afrofuturism
- Kenna – Romantasy, found family, morally gray characters
- Toni – Queer speculative fiction, magical realism, graphic novels
- Linda – Cozy mysteries, historical fiction, book club picks
Key Findings
- Fantasy & Romantasy dominate viral trends, especially in series form.
- Over 50% of viral books feature diverse representation.
- Series drive more engagement than standalones.
- Adaptation buzz fuels virality – even indie titles can land screen deals.
- Viral momentum is reader-driven, not just marketing-led.
Challenges & Lessons Learned
Working with small data and multiple APIs brought challenges:
- Messy metadata required extensive cleaning and custom mapping.
- Some API responses were unreliable, requiring error handling and manual checks.
- Defining tagging standards earlier would have streamlined the process.