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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
Emergence and Breaking of Echo Chambers in Social Systems

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.