# The Enron Corpus: Where the Email Bodies are Buried?

arXiv: https://arxiv.org/abs/2001.10374 · HTML: https://mlsanity.com/paper/2001.10374/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Jan 2020.

## Built on by (most cited first, 2 of 2)

- [BEAVER: An Efficient Deterministic LLM Verifier](https://mlsanity.com/paper/2512.05439/) (2025)
- [The Text Beside the Image: Detection, Utility and Leakage for Trustworthy Multimodal Medical Data and Beyond](https://mlsanity.com/paper/2609.33280/) (2026)

## Abstract (arXiv)

To probe the largest public-domain email database for indicators of fraud, we apply machine learning and accomplish four investigative tasks. First, we identify persons of interest (POI), using financial records and email, and report a peak accuracy of 95.7%. Secondly, we find any publicly exposed personally identifiable information (PII) and discover 50,000 previously unreported instances. Thirdly, we automatically flag legally responsive emails as scored by human experts in the California electricity blackout lawsuit, and find a peak 99% accuracy. Finally, we track three years of primary topics and sentiment across over 10,000 unique people before, during and after the onset of the corporate crisis. Where possible, we compare accuracy against execution times for 51 algorithms and report human-interpretable business rules that can scale to vast datasets.