This work is dedicated to describing the methodology of forming semantic network structures related to the main characters of a book and various concepts of the subject area. The methodology is based on the use of the chatGPT system, trained by a linguistic network, so no formulas or explicitly assigned calculations are used in the article. The methodology includes visualization of the formed networks. For this purpose, the Gephi (gephi.org) program is used. The CSV format is suitable for loading data into the Gephi environment, so all prompts to Chat GPT are accompanied by a data format requirement. The article shows the possibility of building concept networks based on the use of Chat GPT, solving tasks that were previously solved with the involvement of large temporal and human resources. It demonstrates how means of intelligent text analysis and network analysis are integrated, as well as their visualization. For the first time, the emulation of a group of experts is proposed by repeatedly building prompts to the ChatGPT system. As a result, a comprehensive methodology is proposed and tested, which can be applied for network analysis of literary works and building models of various subject areas. Keywords: Chat GPT, Concept networks, Graph visualization, Book network analysis, Domain model, Artificial experts, Information law