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Emergence and Breaking of Echo Chambers in Social Systems
Collective Systems
Modelling & Sim
Python
AI & ML
Agent-Based Modeling
Probabilistic Modeling
Network Science
Multi-Agent Systems
Complex Systems
Data Analysis
About
Overview
This research studies the challenge of echo chambers in networked systems, focusing on how homophily drives polarization and prevents consensus.
Methodology
- Agent-Based Simulations: Modeled the emergence of echo chambers.
- Complex Systems Analysis: Analyzed the dynamics of social systems.
- Messengers Strategy: Explored a novel strategy using a Dichotomous Markov Process to break echo chambers.
- Scalability: Provided a scalable framework for understanding social dynamics.