gca-analyzer 0.4.1

A package for Group Conversation Analysis with improved text processing and visualization

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GCA Analyzer

Introduction

GCA Analyzer is a Python package for analyzing group conversation dynamics using NLP techniques and quantitative metrics.

Features

• Multi-language Support: Built-in support for Chinese and other languages through LLM models
• Comprehensive Metrics: Analyzes group interactions through multiple dimensions
• Automated Analysis: Finds optimal analysis windows and generates detailed statistics
• Flexible Configuration: Customizable parameters for different analysis needs
• Easy Integration: Command-line interface and Python API support

Quick Start

Installation

# Install from PyPI
pip install gca-analyzer

# For development
git clone https://github.com/etShaw-zh/gca_analyzer.git
cd gca_analyzer
pip install -e .

Basic Usage

1. Prepare your conversation data in CSV format with required columns:

conversation_id,person_id,time,text
1A,student1,0:08,Hello teacher!
1A,teacher,0:10,Hello everyone!

2. Run analysis:

python -m gca_analyzer --data your_data.csv

3. Descriptive statistics for GCA measures:

The analyzer generates comprehensive statistics for the following measures:

• Participation

  • Measures relative contribution frequency
  • Negative values indicate below-average participation
  • Positive values indicate above-average participation

• Responsivity

  • Measures how well participants respond to others
  • Higher values indicate better response behavior

• Internal Cohesion

  • Measures consistency in individual contributions
  • Higher values indicate more coherent messaging

• Social Impact

  • Measures influence on group discussion
  • Higher values indicate stronger impact on others

• Newness

  • Measures introduction of new content
  • Higher values indicate more novel contributions

• Communication Density

  • Measures information content per message
  • Higher values indicate more information-rich messages

Results are saved as CSV files in the specified output directory.

Citation

If you use this tool in your research, please cite:

@software{gca_analyzer,
  title = {GCA Analyzer: Group Conversation Analysis Tool},
  author = {Xiao, Jianjun},
  year = {2025},
  url = {https://github.com/etShaw-zh/gca_analyzer}
}