Friendship Prediction on Social Network Users

Abstract

Undoubtedly friendship is one of key factors which keep social networking service users active and the whole community expanding. Hence, predicting friendships becomes an indispensable service provided by the platforms like Plurk, Twitter and Facebook. In this study, an empirical prediction resolution is presented by taking into account the interactions among Plurk users in Taiwan. Both response links and content information extracted from the interaction corpus are used as features in the implementation of the vector space machine based prediction. Experimental results show that the presented approach outperforms those bag-of-word based methods presented in previous studies.