Automatic generation of DRI Statements

TL;DR

This paper presents an automated NLP-based method for generating DRI statements, significantly reducing manual effort and enabling more efficient assessment of group deliberation quality.

Contribution

It introduces a systematic framework utilizing large language models for automated DRI statement generation, advancing social science research methodologies.

Findings

Automated DRI statement generation reduces human effort.

Framework enables scalable assessment of deliberative processes.

Provides a replicable AI integration template for social sciences.

Abstract

Assessing the quality of group deliberation is essential for improving our understanding of deliberative processes. The Deliberative Reason Index (DRI) offers a sophisticated metric for evaluating group reasoning, but its implementation has been constrained by the complex and time-consuming process of statement generation. This thesis introduces an innovative, automated approach to DRI statement generation that leverages advanced natural language processing (NLP) and large language models (LLMs) to substantially reduce the human effort involved in survey preparation. Key contributions are a systematic framework for automated DRI statement generation and a methodological innovation that significantly lowers the barrier to conducting comprehensive deliberative process assessments. In addition, the findings provide a replicable template for integrating generative artificial intelligence into social science research methodologies.