Data Science Applications in the Regulatory Impact Assessment

Authors

  • Peerapat Chokesuwattanaskul Faculty of Law, Chulalongkorn University
  • Sadanan Arsaibun Faculty of Arts, Chulalongkorn University
  • Attapol Thamrongrattanarit Faculty of Arts, Chulalongkorn University

Keywords:

artificial intelligence, data science, natural language processing, sentiment analysis, legal infomatics, public hearing, The Rules for Drafting Laws and Evaluating the Effectiveness of the Law Act B.E. 2562, regulatory impact assessment, topic modeling

Abstract

The Rules for Drafting Laws and Evaluating the Effectiveness of the Law Act B.E. 2562, issued in accordance with the principle of section 77 of the Constitution of the Kingdom of Thailand, has laid the principles for analysing the impact and evaluating the effectiveness of the law. It places great importance on the public hearing process by requiring responsible government agencies to conduct public hearings through the Central System. However, the resources and capability to thoroughly analyse the data vary across government agencies and contexts. Moreover, the analysis of language data is tremendously time- and resource-consuming, especially when compared with structured or quantitative data. Therefore, this paper presents a study method to extract insights from the unstructured public-hearing data using artificial intelligence and Natural Language Processing (NLP) knowledge. We exhibit the analysis by applying two NLP techniques to the Student Loan Fund Act B.E. 2560: Topic modeling and Sentiment analysis. This paper demonstrates the benefits and serves as guidelines to analyse the data collected from the public hearing process under the B.E. 2562 RIA Act and other potential contexts.

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Published

2023-06-30

Issue

Vol. 52 No. 2 (2566): Thammasat Law Journal

Section

Articles

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