Social networks contain plenty of people (or actors) who build certain links or ties. It allows us to call these websites social structures and analyze them using networks or graph theory. A sociogram obtained in the result looks like a picture with a lot of dots (actors) connected by lines (ties). Social network analysis is based on a set of theoretical perspectives. In brief, they require focusing on the links between the actors rather than on actors themselves. Individual actors matter only when combined with others. The outcome of the analysis always depends on the structure.
Visualization of network by means of its analysis is important to understand the data it contains. Though blamed to be purely theoretical, social network analysis has a number of applications. It is commonly used in data mining, telecommunications, social and behavioral studies. Analysis of customers and their relations is required practically in every business, including construction, healthcare, software, social media etc. Computer-supported collaborative learning is a new field where social network analysis is successfully applied. It helps to better understand how students collaborate and communicate.