To enrich word embedding with concept representations, we propose a dynamic context-aware affective graph attention mechanism to compute the concept representation for each token.
the concept representation c(t) ∈ R d for token t is computed as where c k ∈ R d denotes the concept embedding of c k and α k denotes its attention weight.