Inspired by the models above, the goal of this research is to build a model for exploiting syntax, semantic, sentiment and context of tweets by constructing four kinds of embeddings: Char-AVs, LexW2Vs, ContinuousW2Vs and Depen-dencyW2Vs.
we modify Bi-GRNN of (Chung et al., 2014) into Bi-CGRNN to take word embeddings in order to produce a sentence-wide representation from sentence compositions.