  Sarcasm is a form of communication in whichthe person states opposite of what
he actually means. It is ambiguous in nature. In this paper, we propose using
machine learning techniques with BERT and GloVe embeddings to detect sarcasm in
tweets. The dataset is preprocessed before extracting the embeddings. The
proposed model also uses the context in which the user is reacting to along
with his actual response.
