# Creation and Analysis of an International Corpus of Privacy Laws

arXiv: https://arxiv.org/abs/2206.14169 · HTML: https://mlsanity.com/paper/2206.14169/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 80 references that are in the map.
- First posted on arXiv 28 Jun 2022.

## Builds on (most cited first, 12 of 12)

- [LexGLUE: A Benchmark Dataset for Legal Language Understanding in English](https://mlsanity.com/paper/2110.00976/) (2021)
- [Lawformer: A Pre-trained Language Model for Chinese Legal Long Documents](https://mlsanity.com/paper/2105.03887/) (2021)
- [ILDC for CJPE: Indian Legal Documents Corpus for Court Judgment Prediction and Explanation](https://mlsanity.com/paper/2105.13562/) (2021)
- [Question Answering for Privacy Policies: Combining Computational and Legal Perspectives](https://mlsanity.com/paper/1911.00841/) (2019)
- [A Dataset for Statutory Reasoning in Tax Law Entailment and Question Answering](https://mlsanity.com/paper/2005.05257/) (2020)
- [Polisis: Automated Analysis and Presentation of Privacy Policies Using Deep Learning](https://mlsanity.com/paper/1802.02561/) (2018)
- [Privacy Policies over Time: Curation and Analysis of a Million-Document Dataset](https://mlsanity.com/paper/2008.09159/) (2020)
- [Corpus for Automatic Structuring of Legal Documents](https://mlsanity.com/paper/2201.13125/) (2022)
- [Privacy at Scale: Introducing the PrivaSeer Corpus of Web Privacy Policies](https://mlsanity.com/paper/2004.11131/) (2020)
- [Robust Deep Reinforcement Learning for Extractive Legal Summarization](https://mlsanity.com/paper/2111.07158/) (2021)
- [PyEuroVoc: A Tool for Multilingual Legal Document Classification with EuroVoc Descriptors](https://mlsanity.com/paper/2108.01139/) (2021)
- [Orchestrating NLP Services for the Legal Domain](https://mlsanity.com/paper/2003.12900/) (2020)

## Built on by (most cited first, 3 of 3)

- [A Systematic Evaluation of Traditional Privacy Policy Analysis Tools Against LLMs](https://mlsanity.com/paper/2607.17075/) (2026)
- [Enabling Multilingual Privacy Policy Audits: Large-Scale Analysis of Spanish Mobile Apps](https://mlsanity.com/paper/2607.18424/) (2026)
- [SoK: From Generation to Consumption of Privacy Documents in Software Systems](https://mlsanity.com/paper/2608.12511/) (2026)

## Abstract (arXiv)

The landscape of privacy laws and regulations around the world is complex and ever-changing. National and super-national laws, agreements, decrees, and other government-issued rules form a patchwork that companies must follow to operate internationally. To examine the status and evolution of this patchwork, we introduce the Government Privacy Instructions Corpus, or GPI Corpus, of 1,043 privacy laws, regulations, and guidelines, covering 182 jurisdictions. This corpus enables a large-scale quantitative and qualitative examination of legal foci on privacy. We examine the temporal distribution of when GPIs were created and illustrate the dramatic increase in privacy legislation over the past 50 years, although a finer-grained examination reveals that the rate of increase varies depending on the personal data types that GPIs address. Our exploration also demonstrates that most privacy laws respectively address relatively few personal data types, showing that comprehensive privacy legislation remains rare. Additionally, topic modeling results show the prevalence of common themes in GPIs, such as finance, healthcare, and telecommunications. Finally, we release the corpus to the research community to promote further study.