Graph-Based Social Network Analysis

The whole world today has become a global entity with everything accessible from the palm of our hands and touch screen. As the world today becomes more and more connected, it is more important than ever to analyze interconnected relationships and measure the strength of relationships in different ways. Social Network Analysis (SNA) has become a very effective and useful tool for analyzing the network relationships that exist between actors and reactors in dynamic relationships. SNA, also known as network science, is a field of data analysis that uses networks and graph theory to understand social structures. A growing number of social networks are evolving and changing daily, such as online social media, science affiliate networks, airport transit networks, etc. Members of social networking sites communicate with each other. They may create new connections or break existing connections, triggering the emergence of complex network structures.

Additionally, dynamics in social media, such as ideology, distribution flexibility, and shared behavior, result in interpersonal communication and interaction. This can lead to complex events, which demonstrate the basic role of social networks as a complex system. Analyzing complex human behavior and mining topology can help to understand the important mechanism of macroscopic events. This will help attract public interest and provide early warning of joint emergencies. Therefore, social media mines have become a promising research site and are attracting a lot of attention. Social networks have dramatically changed the way people produce and use online information, further reducing the access barrier and allowing for new forms of interaction between people, objects, information, and services. The COVID epidemic has proven that such communication can be extremely important when communication needs to be reduced and human movement restricted.