Analysis of Relations in eLearning

This paper is focused on searching for socials networks in eLearning system data. This data does not create a social network from the beginning, but contains records about student activity in an eLearning system. There are latent ties in these collections, which we also interpret as social network. We discovered  these latent ties via clustering methods and, consequently, we used methods for social network analyses. The social networks we analyzed in this paper are represented by groups of students who have similar contacts and interact in similar social circles.