  In the age of digital interaction, person-to-person relationships existing on
social media may be different from the very same interactions that exist
offline. Examining potential or spurious relationships between members in a
social network is a fertile area of research for computer scientists -- here we
examine how relationships can be predicted between two unconnected people in a
social network by using area under Precison-Recall curve and ROC. Modeling the
social network as a signed graph, we compare Triadic model,Latent Information
model and Sentiment model and use them to predict peer to peer interactions,
first using a plain signed network, and second using a signed network with
comments as context. We see that our models are much better than random model
and could complement each other in different cases.
