EmotionEcho.exe presents a three‑phase interactive simulation that demonstrates how algorithmic filtering influences our emotional experiences online. The experience starts with a contemplative narrative about echo chambers, then progresses to a 2D p5.js prototype featuring colored bubbles that symbolize users drawn by emotional forces. The final stage places players in a 3D Unreal Engine world, allowing them to explore and manipulate emotional feedback cycles in real time.

The technical implementation involves extracting TikTok posts and comments through Python and BeautifulSoup, categorizing sentiment with a multilingual model, and measuring emotion uniformity using OLS regression. The 2D prototype renders emotional clustering in p5.js, while the complete 3D game utilizes Rhino/Grasshopper for environment creation and Unreal Engine 5 for gravity‑based interactions. Through the integration of data extraction, machine learning, and immersive gameplay, EmotionEcho.exe converts abstract emotional data into a concrete, critical experience.