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With the increased use of social media platforms by people across the world,many new interesting NLP problems have come into existence. One such being thedetection of sarcasm in the social media texts. We present a corpus of tweetsfor training custom word embeddings and a Hinglish dataset labelled for sarcasmdetection. We propose a deep learning based approach to address the issue ofsarcasm detection in Hindi-English code mixed tweets using bilingual wordembeddings derived from FastText and Word2Vec approaches. We experimented withvarious deep learning models, including CNNs, LSTMs, Bi-directional LSTMs (withand without attention). We were able to outperform all state-of-the-artperformances with our deep learning models, with attention based Bi-directionalLSTMs giving the best performance exhibiting an accuracy of 78.49%.

"Did you really mean what you said?" : Sarcasm Detection in Hindi-English Code-Mixed Data using Bilingual Word Embeddings