抄録
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.
