People are social entities. They build complex relationships with others around them, form communities and social circles, belong to organizations. Every decision to make a connection to others is based a large variety of variables (called attributes). Every connection, in turn, affects people’s attitudes, behavior, and actions. This relationship between the structure of people’s connections to others and everything that this structure affects is called social dynamics. Social dynamics is the focus of social network analysis. In this course, we will introduce this exciting field, starting with the very basics – the definitions of network concepts. You will quickly learn that network analysis allows to answer questions and find insights not available with any other approaches. In business, where relationships are essential to efficiency and effectiveness of an organization, it is crucial that analysts know how to analyze these relationships. Therefore, we will not only show you the network concepts, but apply them immediately to real-life business datasets. The possibilities of network analysis are quite broad. In this course, we divide the complex field according to the three major theoretical concepts in social relations: social selection, social influence, and community building. Models of social influence help explain why networks can affect individual behavior. Models of social selection help us understand how people create their network. Community detection models allow us to find the communities that people build, to better understand the structure of such communities. Taken together with network statistics, these models are being demonstrated on real-life datasets collected in real companies. Learners can immediately see how much more powerful relational analysis (networks) are relative to standard statistics alone. They are designed to illustrate some of the specific state-of-the-art approaches within the broader areas. This Course is part of HSE University Master of Data and Network Analytics degree program. Learn more about admission into the program and how your Coursera work can be leveraged if accepted into the program here https://inlnk.ru/WMKM6.