Introduction

Welcome to TWONy-macro, an interactive demonstration that shows how network structure and algorithmic choices shape opinion formation in online communities. Watch as virtual agents with evolving sentiment states interact in a 3D network visualization, creating patterns of opinion convergence, clustering, and polarization. This simulation helps visualize how the topology of social networks and recommendation algorithms influence the collective emotional dynamics of digital communities.

Explore different neighbor selection strategies - from random interactions to similarity-based or sentiment-biased connections - and observe how these algorithmic choices dramatically affect whether communities converge toward consensus or fragment into opposing camps. Everything runs locally in your browser using advanced 3D graphics and real-time opinion dynamics modeling.

How It Works

This simulation implements the Deffuant-Weisbuch Bounded Confidence Model, where virtual agents only influence each other's opinions if they're within a certain "confidence threshold" and can be configured through the following features:

• Network Configuration
  • Number of Agents: Size of the social network (5-500 nodes)
  • Number of Neighbors: Connectivity degree for each agent (1-5 connections)
• Opinion Dynamics (Deffuant-Weisbuch BCM)
  • Epsilon BCM: Confidence threshold for opinion influence (0.01-1.0)
  • Delta BCM: Influence strength parameter (0.01-1.0)
  • Sorting Strategy: Algorithm for neighbor selection during interactions
• Simulation Control
  • Number of Steps: Total simulation duration (50-1000 iterations)
  • Real-time Controls: Start, pause, and reset functionality
  • Progress Tracking: Current step and network evaluation metrics

This educational tool demonstrates core concepts from computational social science, helping users understand how algorithmic design choices in social media platforms can inadvertently shape the emotional landscape of online discourse.