Utilizing Generative AI in Text Analysis

Abstract

The rapid advancement of generative AI in recent years has been remarkable. It has been found that, despite certain limitations and challenges, generative AI can interpret co-occurrence network diagrams, a task traditionally requiring a considerable level of expertise in text analysis. This paper takes the analysis a step further by investigating the extent to which generative AI can propose solutions based on the features identified through the interpretation of co-occurrence network diagrams. A comparative evaluation is conducted between the proposals generated by AI and those made by human experts, aiming to assess the potential of AI in contributing to problem-solving within text analysis.