Since such semantic similarity is but one of the components of context incongruity and since existing feature sets rely on sentiment-based features to capture context incongruity, it is imperative that the two be combined for sarcasm detection.
our paper deals with the question: Can word embedding-based features when augmented to features reported in prior work improve the performance of sarcasm detection?