These observations motivate us to develop a neural model which can operate on the dependency tree of a sentence, with the aim to make accurate sentiment predictions with respect to specific aspects.
we propose a convolution over a dependency tree (CDT) model which exploits a GCN to model the structure of a sentence through its dependency tree, where node (word) embeddings of the tree are initialized by means of a Bi-directional Long Short Term Memory (Bi-LSTM) network.