Home▸Society & Economics▸Filter Bubbles: Recommender-Biased Opinion Dynamics

🫧 Filter Bubbles: Recommender-Biased Opinion Dynamics

Interactive 3D social network where adjusting a recommendation algorithm's bias strength shows simulated agents' opinions clustering into increasingly isolated filter bubbles over time.

Society & Economics3DModerate60 FPS

A 3D social network where every agent's position and colour encode a two-dimensional opinion, and a tunable recommender algorithm decides which peers' views each agent gets shown — watch the population fracture into isolated filter bubbles as bias increases.

🔬 What It Demonstrates

Amber lines flash between agents to show live "recommendations." When the recommender favours opinion-similar peers, agents keep updating toward people who already agree with them, so clusters compact and drift apart — a visible feedback loop between ranking algorithms and opinion polarization.

🎮 How to Use

Raise recommender bias to see homophily-driven clustering accelerate; raise diversity injection to counteract it with random exposure. Adjust social influence and simulation speed, then watch the polarization and bubble-count stats update live.

💡 Did You Know?

Researchers studying real recommender systems find that a small amount of injected randomness can meaningfully reduce echo-chamber formation without much hurting engagement — exactly the trade-off the diversity slider models here.

⚙ Under the hood

Interactive 3D social network where adjusting a recommendation algorithm's bias strength shows simulated agents' opinions clustering into increasingly isolated filter bubbles over time.

filter-bubblesrecommender-systemsopinion-dynamicssocial-networkspolarizationsociety

3D · Three.js / WebGL renderer · 60 FPS target · runs fully client-side, no install