Tracking Amendments to Legislation and Other Political Texts with a Novel Minimum-Edit-Distance Algorithm: DocuToads
This provides a more efficient solution for political scientists tracking legislative amendments, though it is incremental as it builds on existing minimum-edit-distance concepts.
The study tackled the problem of tracking amendments to political texts by introducing two novel minimum-edit-distance algorithms, which detect types and amounts of changes between text versions. The results showed these methods produce superior measures compared to hand-coded efforts, reducing time and resource costs significantly.
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.