  In recent decades, the emergence of social networks has enabled internet
service providers (e.g., Facebook, Twitter and Uber) to achieve great
commercial success. Link prediction is recognized as a common practice to build
the topology of social networks and keep them evolving. Conventionally, link
prediction methods are dependent of location information of users, which
suffers from information leakage from time to time. To deal with this problem,
companies of smart devices (e.g., Apple Inc.) keeps tightening their privacy
policy, impeding internet service providers from acquiring location
information. Therefore, it is of great importance to design location free link
prediction methods, while the accuracy still preserves. In this study, a novel
location free link prediction method is proposed for complex social networks.
Experiments on real datasets show that the precision of our location free link
prediction method increases by 10 percent.
