# Tracking Amendments to Legislation and Other Political Texts with a Novel Minimum-Edit-Distance Algorithm: DocuToads

arXiv: https://arxiv.org/abs/1608.06459 · HTML: https://mlsanity.com/paper/1608.06459/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Aug 2016.

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

- [The Character Error Vector: Decomposable errors for page-level OCR evaluation](https://mlsanity.com/paper/2604.06160/) (2026)

## Abstract (arXiv)

Political scientists often find themselves tracking amendments to political texts. As different actors weigh in, texts change as they are drafted and redrafted, reflecting political preferences and power. This study provides a novel solution to the prob- lem of detecting amendments to political text based upon minimum edit distances. We demonstrate the usefulness of two language-insensitive, transparent, and efficient minimum-edit-distance algorithms suited for the task. These algorithms are capable of providing an account of the types (insertions, deletions, substitutions, and trans- positions) and substantive amount of amendments made between version of texts. To illustrate the usefulness and efficiency of the approach we replicate two existing stud- ies from the field of legislative studies. Our results demonstrate that minimum edit distance methods can produce superior measures of text amendments to hand-coded efforts in a fraction of the time and resource costs.