Network Visualization of ChatGPT Research: a study based on term and keyword co-occurrence network analysis
This provides a network visualization tool for library and information science and IT professionals to understand ChatGPT research trends.
The study identified major research areas of ChatGPT by analyzing term and keyword co-occurrence networks from 577 publications, finding that 'chatgpt' occurred most frequently followed by related terms like artificial intelligence and large language models.
The main objective of this paper is to identify the major research areas of ChatGPT through term and keyword co-occurrence network mapping techniques. For conducting the present study, total of 577 publications were retrieved from the Lens database for the network visualization. The findings of the study showed that chatgpt occurrence in maximum number of times followed by its related terms such as artificial intelligence, large language model, gpt, study etc. This study will be helpful to library and information science as well as computer or information technology professionals.