Sarcasm Detection Using Deep Convolutional Neural Networks: A Modular Deep Learning Framework

Abstract--Sarcasm is a nuanced and often misinterpreted form of communication, especially in text, where tone and body language are absent. This paper presents a proposed modular deep learning framework for sarcasm detection, leveraging Deep Convolutional Neural Networks (DCNNs) and contextual models like BERT to analyze linguistic, emotional, and contextual cues [1][2]. The system is conceptually designed to integrate sentiment analysis, contextual embeddings, linguistic feature extraction, and emotion detection through a multi-layer architecture. Although the model is not yet implemented, the design demonstrates feasibility for real-world applications like chatbots and social media monitoring [9][11]. Sarcasm detection is vital for enhancing the interpretabil-ity of automated systems like sentiment analyzers, chatbots, and recommendation engines [9][13].