查看文章

Today, with the advancement of communication technologies, particularly the Internet, we are witnessing the generation of a vast amount of information. In academic research, it is crucial to identify the most frequently studied topics and challenges in each field, as well as to determine their significance. One way to evaluate scientific research in any field is by analyzing its scientific map. One of the most effective methods for visualizing and analyzing a scientific map is to utilize network analysis approaches. This technique can effectively demonstrate the structure of scientific networks. 

In this study, we visualized and analyzed the scientific network of articles published in the journal "Research in School and Virtual Learning" using network and co-word analysis methods. A total of 227 articles were included in the analysis. The general research approach includes collecting and cleaning data, constructing matrices of scientific networks, and analyzing and evaluating the results. Various scientific networks of articles, including the co-authorship network, co-organization network, semantic network of articles, and co-occurrence network of words, have been analyzed. PHP language was used for data crawling and processing, while Python language and Gephi software were utilized for network-based analysis and visualization of different networks. In addition, a proposed approach based on the TF-IDF method has been used to calculate the adjacency matrices of each network. This approach includes ten steps. 1) Integrating the title, keywords, and abstract of each article. 

The findings reveal the extent of semantic …