Sarcasm, a standard social media message, delivers the opposite meaning through irony or teasing. Unfortunately, identifying sarcasm in written text is difficult in natural language processing. The work aims to create an effective sarcasm detection model for social media text data, with possible applications in sentiment analysis, social media analytics, and online reputation management. A hybrid Deep learning strategy is used to construct an effective sarcasm detection model for written content on social media networks. The design emphasizes f...eature extraction, selection, and neural network application. Limited research exists on detecting sarcasm in human speech compared to emotion recognition. The study recommends using Word2Vec or TF-IDF for feature extraction to address memory and temporal constraints. Use feature selection techniques like PCA or LDA to enhance model performance by selecting relevant features. A Capsule Neural Network (CNN) and Long Short-Term Memory (LSTM) collect contextual information and sequential dependencies in textual material. We evaluate Reddit datasets with labelled sarcasm data using metrics like Accuracy. Our hybrid method gets 95.60% accuracy on Reddit.Read more

This study provides a novel way to detect duplicate questions in the Stack Overflow community, posing a daunting problem in natural language processing. Our proposed method leverages the power of deep learning by seamlessly merging Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks to capture both local nuances and long-term relationships inherent in textual input. Word embeddings, notably Google’s Word2Vec and GloVe, raise the bar for text representation to new heights. Extensive studies on the Stack Overflow ...dataset demonstrate the usefulness of our approach, generating excellent results. The combination of CNN and LSTM models improves performance while streamlining preprocessing, establishing our technology as a viable piece in the arsenal for duplicate question detection. Aside from Stack Overflow, our technique has promise for various question-and-answer platforms, providing a robust solution for finding similar questions and paving the path for advances in natural language processing.Read more