CEU Electronic Theses and Dissertations, 2024
| Author | Shatilov, Vladislav |
|---|---|
| Title | From Proposal to Policy: Assessing the Relationship between Public Comments and US Federal Regulations Using Natural Language Processing |
| Summary | Public commenting has become very important in regulatory policy globally, aiming to enhance regulation quality and transparency. Despite widespread adoption and substantial engagement from both the public and governmental bodies, the association between public commenting and regulation revisions remains underexplored. Existing research offer limited generalizability by focusing narrowly on specific domains or using small datasets. To address these gaps, this research introduces a novel approach that evaluates the relationship between the content of public comments and changes in regulatory texts in the United States. Multiple text similarity techniques are utilized to compare the initial and final versions of regulations. The analysis employs multiple regression to analyse the relationship and a machine learning model to detect non-linear patterns of it. Key variables examined include the share of words by which differ two versions of regulations in comments, the volume of comments, and their emotional tone. The key finding is that larger revisions of regulatory texts are strongly associated with greater stakeholders’ attention to the subsequently revised parts, while the effect of other factors is unclear or minimal. |
| Supervisor | Fazekas, Mihály |
| Department | Public Policy MPA |
| Full text | https://www.etd.ceu.edu/2024/shatilov_vladislav.pdf |
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