Simulating systematic bias in attributed social networks and its effect on rankings of minority nodes
Abstract Network analysis provides powerful tools to learn about a variety of social systems.However, most analyses implicitly assume that the considered relational data is error-free, and reliable and accurately reflects the system to be analysed.Especially if the network consists of multiple groups (e.g., genders, races), this assumption conflict