Network Modeling Methods for Semantic Memory Structure: A Theoretical Review

The article is aimed at considering the network modeling methods for human semantic memory structure. The work provides an analytical review of existing approaches to modeling the structure of human semantic memory, as a result of which the most methodologically optimal way of modeling semantic memory is estab-lished – based on the construction and analysis of semantic networks. The authors study various methods of network modeling of semantic memory structure: verbal fluency problem, snowball problem, semantic connec-tivity problem. In addition, examples of using these methods in psychological research are given, and their methodological advantages and disadvantages are highlighted. The results of the present work can be useful in the formation of new methods for network modeling of the structure of human semantic memory, as well as in the creation of intelligent systems that process graph data.