Discovering the Structure of Knowledge in Urban Data Mining Using Vocabulary Co-occurrence Analysis

The co-occurrence technique of words is used to illustrate the structure of knowledge in new scientific fields. In the current study, which is development in terms of purpose and descriptive-analytical in terms of method; It is taken from the co-occurrence analysis of words for further analysis and understanding of the field of urban data mining. Therefore, in this study, the trend of scientific productions and leading authors in this field has been examined. And then the most important components of the structures of this new field of scientific articles are presented. For this purpose, 392 articles in the field of urban data mining were found after searching the reference database of Web of Science, and statistical methods and VOSviewer software were used to analyze the information of these articles. The results show that the most influential and leading country in this field is China, whose researchers have published 28 articles in the science citation database. Also, the analysis of the time course of the articles shows that this topic has been around for a decade and the more we move to the present, the growth of scientific productions in this field will increase. But the most important finding of the current research, which was obtained based on clustering analysis and knowledge map analysis, shows that the field of urban data mining has five subfields or main structural components: 1-Analysis of urban systems and smart cities, 2- Modeling and data analysis framework, 3- identifying patterns and predicting them along with visualization techniques, 4- big data and social media, 5- urban big data and traffic network; Of these, urban big data analysis is more recent than other sub-structures, and research in this field is mostly related to the years 2022 and 2023.