📽️ Dynamic Visualization of the Legislative Network This repository contains code and output for a dynamic visualization of the New Zealand legislative network, with a focus on the Mental Health (Compulsory Assessment and Treatment) Act 1992.

The notebook Dynamic_visualization_MentalHealthAct.ipynb generates an animated representation of how the structure and relationships between Acts evolve over time. Using preprocessed CSV files containing legal network and centrality data, the animation reflects monthly changes across 20 act versions.

The animation captures:

Node additions and removals

Legal relationship evolution (citations, amendments, repeals)

Temporal dynamics of the legislative environment

⚙️ Requirements To run the visualization script, ensure you have the following:

Python 3.8+

Jupyter Notebook

Manim Community Edition

pandas

networkx

matplotlib

The animation is rendered using Manim’s OpenGL engine for smooth and high-quality transitions.

🎞️ Output MentalHealthAct_Network_Animation.mp4 This is the final video output illustrating the monthly evolution of the legislative network. It shows the dynamic interplay of legal relationships and structural changes around the core act over time.

📊 Information Extraction and Network Analysis The notebook Information_Extraction.ipynb contains code for Named Entity Recognition, Relation Extraction, Katz Prestige Centrality, Louvain Community Detection Algorithm, Agglomerative Clustering, and Content Similarity using Jaccard Similarity. These methods are used to identify the best parliamentary committee label for each macro community based on LDA keywords, providing deeper insights into the structure and thematic organization of the legislative network.