Skip to content

Research Visualizations & Network Analysis

Overview

Counterforce-One research includes powerful visualization methods to understand health misinformation patterns and community resilience. Our research methodology includes both interactive dashboards and detailed network visualizations to analyze community dynamics.

Research Network Diagrams

Our research methodology includes 4 detailed network diagrams corresponding to our key case studies:

Case Study Network Visualizations

  1. "U=U, 100%!" Network - Research visualization of how accurate HIV treatment information spreads with community nuance
  2. "HIV is life altering..." Network - Analysis of the challenge of identifying and correcting subtle misinformation
  3. "was recently diagnosed with hiv" Network - Study of peer support patterns and community response
  4. "prep exists folks weird about condoms" Network - Research into knowledge gaps and community education opportunities

Each network diagram reveals: - Comment reply relationships - Communication patterns between users - Node size by comment score - Influence and engagement indicators - Community resilience indicators - How communities respond to health information

Research Showcase Interface

The public research showcase presents these findings in an accessible format for academic and public health audiences. The showcase includes:

  • Interactive case study exploration
  • Network diagram integration
  • Research finding summaries
  • Methodology explanation

Research Data Access

The research visualizations are generated from data located in: 

data/demo_visualizations/
├── network_1ls1tyz.html    # U=U network
├── network_1lyphrb.html    # HIV life altering network
├── network_1la8c64.html    # Recently diagnosed network
├── network_1lhs70z.html    # PrEP/condoms network
└── ...

Research Dashboard Features

  • Community Network Maps: Interactive social graphs for relationship analysis
  • Language Distribution: Multilingual content pattern analysis
  • Temporal Analysis: Time-series health discussion trends
  • Support Network Visualization: Community resilience indicators

Technical Implementation

The visualization tools are implemented using the following technical components:

  • Network Visualization: Built with NetworkX and Plotly for interactive exploration
  • Data Processing: Python-based analysis pipeline with PostgreSQL backend
  • Web Interface: Gradio-based interfaces for research access

Generating Research Visualizations

To generate additional research visualizations for analysis:

python tools/generate_demo_visualizations.py

This will create new network diagrams and other visualizations based on your current research dataset.