Evaluating knowledge flow in multirelational scientific social networks

Social networks are dynamic social structures consisting of individuals or organizations, usually represented by nodes tied by one or more types of relationships. Analyzing these structures allows us to detect several inter and intra connections between people, inside and outside their organizations. In this context, we construct a multi-relational scientific social network where researchers may have four different types of relationships with each other. Using clustering techniques with max flow measure, we identify the social structure and research communities in a way that allows us to evaluate the knowledge flow in the Brazilian scientific scenario of the Computing Sciences.