# Unveiling Themes in Judicial Proceedings: A Cross-Country Study Using Topic Modeling on Legal Documents from India and the UK

arXiv: https://arxiv.org/abs/2406.00040 · HTML: https://mlsanity.com/paper/2406.00040/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 29 references that are in the map.
- First posted on arXiv 27 May 2024.

## Builds on (most cited first, 5 of 5)

- [Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks](https://mlsanity.com/paper/1908.10084/) (2019)
- [UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction](https://mlsanity.com/paper/1802.03426/) (2018)
- [BERTopic: Neural topic modeling with a class-based TF-IDF procedure](https://mlsanity.com/paper/2203.05794/) (2022)
- [Legal Case Document Summarization: Extractive and Abstractive Methods and their Evaluation](https://mlsanity.com/paper/2210.07544/) (2022)
- [Combining topic modelling and citation network analysis to study case law from the European Court on Human Rights on the right to respect for private and family life](https://mlsanity.com/paper/2401.16429/) (2024)

## Built on by (most cited first, 1 of 1)

- [Hybrid Topic-Semantic Labeling and Graph Embeddings for Unsupervised Legal Document Clustering](https://mlsanity.com/paper/2509.00990/) (2025)

## Abstract (arXiv)

Legal documents are indispensable in every country for legal practices and serve as the primary source of information regarding previous cases and employed statutes. In today's world, with an increasing number of judicial cases, it is crucial to systematically categorize past cases into subgroups, which can then be utilized for upcoming cases and practices. Our primary focus in this endeavor was to annotate cases using topic modeling algorithms such as Latent Dirichlet Allocation, Non-Negative Matrix Factorization, and Bertopic for a collection of lengthy legal documents from India and the UK. This step is crucial for distinguishing the generated labels between the two countries, highlighting the differences in the types of cases that arise in each jurisdiction. Furthermore, an analysis of the timeline of cases from India was conducted to discern the evolution of dominant topics over the years.