Modeling of social networks using graph theory and fuzzy logic

DOI: 10.31673/2412-9070.2024.051035

Abstract

Social network analysis is a powerful tool for understanding complex interactions in today's world. Its application finds a place in various fields, from marketing to criminology, making it indispensable for research and practical use.
The paper proposes an approach to the analysis and modeling of social networks based on the use of graph databases and fuzzy logic. Modern research confirms the effectiveness of the combination of graph databases and fuzzy logic for the analysis and modeling of social networks, which allows taking into account the complex relationships between objects and improving the accuracy of forecasts. However, the need to develop methods and models for the analysis of social networks, taking into account the non-stationarity and uncertainty of their characteristics determine the relevance of further research in this direction.
The aim of the paper is to formalize social networks using graph theory and fuzzy logic to build information technology for analyzing social networks based on graph databases. Aspects of the use of graph databases and fuzzy logic for the storage and analysis of social network data are considered, the main elements of social networks and their characteristics are highlighted and formalized. The developed model includes the definition of social network accounts as vertices of a weighted graph and their main characteristics, the description of connections between social network accounts in the form of regular and fuzzy binary time-dependent relations. Considered the relationship of subscription, influence and similarity of social network accounts.
The proposed model allows you to analyze the influence of individual accounts and simulate the spread of information, identify types of users to detect abnormal behavior, analyze the dynamics of changes in social networks and predict future trends. The results of the work can be used in marketing, crisis management and security, political campaigns, social sciences and other fields, making social network analysis a more accurate and effective tool for a variety of tasks.

Keywords: social networks, graph database, fuzzy logic, graph theory, analysis, modeling, information technology, information system, data analysis.