Automatic generation of DRI Statements
This work addresses the time-consuming process of DRI implementation for researchers in social science, offering an automated solution to lower barriers for deliberative process assessments.
The paper tackled the problem of automating the generation of Deliberative Reason Index (DRI) statements, which are used to assess group deliberation quality, by developing an approach using NLP and LLMs that substantially reduces human effort in survey preparation.
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.