A Contextual Topic Modeling and Content Analysis of Iranian laws and Regulations

TL;DR

This study applies topic modeling to analyze 11,760 Iranian laws from 2016-2023, revealing dominant themes like economics and customs, and highlighting societal and legislative trends over time.

Contribution

It introduces a large-scale application of LDA for law text analysis, identifying key legal topics and their evolution in Iran from 2016 to 2023.

Findings

Economics laws constitute 29% of regulations.

Cultural laws increased notably in 2023.

Most laws focus on economic and customs issues.

Abstract

A constitution is the highest legal document of a country and serves as a guide for the establishment of other laws. The constitution defines the political principles, structure, hierarchy, position, and limits of the political power of a country's government. It determines and guarantees the rights of citizens. This study aimed at topic modeling of Iranian laws. As part of this research, 11760 laws were collected from the Dotic website. Then, topic modeling was conducted on the title and content of the regularizations using LDA. Data analysis with topic modeling led to the identification of 10 topics including Economic, Customs, Housing and Urban Development, Agriculture, Insurance, Legal and judicial, Cultural, Information Technology, Political, and Government. The largest topic, Economic, accounts for 29% of regulations, while the smallest are Political and Government, accounting for 2%. This research utilizes a topic modeling method in exploring law texts and identifying trends in regularizations from 2016-2023. In this study, it was found that regularizations constitute a significant percentage of law, most of which are related to economics and customs. Cultural regularizations have increased in 2023. It can be concluded any law enacted each year can reflect society's conditions and legislators' top concerns.