NLP4Gov - AI-Powered Computational Policy Analysis

A scalable NLP-based library for empirical policy analysis, developed by the C² Lab at UC Davis. It features pipelines and applications for processing policy documents at scale.

NLP4Gov: AI-Powered Computational Policy Analysis

🔍 GitHub Repository: NLP4Gov on GitHub

📜 Full Paper: Mahasweta Chakraborti, Sailendra Akash Bonagiri, Santiago Virgüez-Ruiz, and Seth Frey. CHI EA ‘24 (Extended Abstracts of the 2024 CHI Conference on Human Factors in Computing Systems)

🚀 Overview

NLP4Gov is an open-source library that provides NLP-based pipelines for computational policy analysis. Developed by the C² Lab at UC Davis, it enables large-scale policy text processing, institutional grammar analysis, and governance comparisons.

🔹 Features & Applications

✅ Policy Text Processing:

  • Preprocesses policy documents using coreference resolution, semantic role labeling, and topic modeling.
  • Handles large-scale policy text datasets with Colab integration.

✅ Institutional Grammar Parsing:

  • Implements Elinor Ostrom’s Institutional Grammar Framework for extracting policy components.
  • Performs semantic clustering of actors, resources, and activities.

✅ Policy Comparison & Evolution:

  • Policy search engine to compare institutional statements across communities.
  • Analyzes policy diffusion over time using semantic similarity models.

✅ Scalable & Modular:

  • Uses HuggingFace Transformers, Sentence-BERT, and BM25 retrieval for efficient policy analysis.
  • Supports Google Colab GPU acceleration for seamless processing.

📌 How to Use NLP4Gov

1️⃣ Clone the Repository
```bash git clone https://github.com/BSAkash/NLP4Gov.git cd NLP4Gov