Identifying Intentionally Duplicative Public Comments Submitted to Proposed Federal Rules
Armour, Karin M.
MetadataShow full item record
Since the public commenting process for proposed federal regulations became primarily web-based, the number of rules receiving extremely high comment volumes has increased substantially; raising concerns about whether computer-generated comments designed to appear as if they represent the input of ordinary citizens could be distorting the regulatory process. As one example, the Consumer Financial Protection Bureau's (CFPB's) Payday, Vehicle Title, and Certain High-Cost Installment Loans Proposed Rule ("Payday Rule") received over one million comments, many of which appear to be from individuals, but are highly similar in wording and structure. Using a sentence-level document feature matrix (DFM) to identify repeated phrases, this analysis found that nearly 70 percent of the reviewed comments were moderately to highly suspicious duplicates. Drawing on the characteristics of these duplicates, this paper presents practical alternatives for federal agencies to prevent and respond to similar risks against the regulatory commenting process in the future.