Rethinking the Link Prediction Problem in Signed Social Networks

No. 1: Thirty-First AAAI Conference On Artificial Intelligence

Volume

Proceedings of the AAAI Conference on Artificial Intelligence, 31

Student Abstract Track

We rethink the link prediction problem in signed social networks by also considering "no-relation" as a future status of a node pair, rather than simply distinguishing positive and negative links proposed in the literature. To understand the underlying mechanism of link formation in signed networks, we propose a feature framework on the basis of a thorough exploration of potential features for the newly identified problem. Grounded on the framework, we also design a trinary classification model, and experimental results show that our method outperforms the state-of-the-art approaches.

10.1609/aaai.v31i1.11096