An Automated Deep Learning Model for Detecting Sarcastic Comments
deep learning; interpretability; machine learning; sarcasm detection; self-attention; social media analysis; social media data
The concept of Natural Language Processing is immensely vast with a wide range of fields in which ideas can be explored and innovations can be developed. An algorithm based on deep learning is used to detect sarcasm in text in this paper. It is usually only possible to detect sarcasm through speech and very rarely through text. 1.3 million comments from Reddit were analyzed, of which half were sarcastic and half were not, and then various deep learning models were applied, such as standard neural networks, CNNs, and LSTM RNNs. The best performing model was LSTM-RNNs, followed by CNNs, and standard neural networks came last. With textual data, it is much harder to understand whether the other person is being sarcastic or not, it can only be understood by listening to their tone of voice or looking at their behaviour. The purpose of this paper is to demonstrate how to detect sarcasm in textual data using deep learning models. 2021 IEEE.
2021 IEEE International Conference on Mobile Networks and Wireless Communications, ICMNWC 2021
Institute of Electrical and Electronics Engineers Inc.
https://doi.org/10.1109/ICMNWC52512.2021.9688410 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125729687&doi=10.1109%2fICMNWC52512.2021.9688410&partnerID=40&md5=e81955d1e9fc781ee63a8ee023a40d35
Jose J., CHRIST University, Department of Data Science, Maharashtra, Pune, India; Preethi N., CHRIST University, Department of Data Science, Maharashtra, Pune, India