Cross-Platform Comparative Studies
Understanding systemic patterns across different platform architectures
This project examines how different platform architectures, algorithms, and affordances shape user behavior and content exposure patterns. We conduct comparative studies across platforms to identify systemic patterns versus platform-specific effects.
Comparing platform ecosystems to understand which observed behaviors stem from platform design versus user preferences and societal factors.
Research focuses include:
- Cross-platform behavioral analysis across YouTube, TikTok, Instagram, and other platforms
- Platform architecture effects on content discovery and consumption patterns
- Algorithmic recommendation comparison across different platform types
- Supply and demand dynamics in news-like content ecosystems
- Youth safety and content pathway analysis across platforms
Our work reveals how platform-specific features interact with universal human behaviors, informing both platform design and regulatory approaches to online safety.