Before revision:  These existing modules were able to solve the problem of capturing inter sentence contextual information but not the intra sentence contextual information .
After revision:  These existing modules were able to solve the problem of capturing inter sentence contextual information but not much work has been done to use inter-sentence contextual information for detecting the same. This paper proposes a new state-of-the-art deep learning architecture that uses a novel Bidirectional Inter-Sentence Contextual Attention mechanism (Bi-ISCA) to capture inter-sentence dependencies for detecting sarcasm in the user-generated short text using only the conversational context .