Abdul Rahaman Wahab Sait1,*, Mohamad Khairi Ishak2
Computer Systems Science and Engineering, Vol.44, No.3, pp. 2553-2567, 2023, DOI:10.32604/csse.2023.029603
Abstract Sentiment analysis (SA) is the procedure of recognizing the emotions related to the data that exist in social networking. The existence of sarcasm in textual data is a major challenge in the efficiency of the SA. Earlier works on sarcasm detection on text utilize lexical as well as pragmatic cues namely interjection, punctuations, and sentiment shift that are vital indicators of sarcasm. With the advent of deep-learning, recent works, leveraging neural networks in learning lexical and contextual features, removing the need for handcrafted feature. In this aspect, this study designs a deep learning with natural language processing enabled SA (DLNLP-SA)… More >
Login
Register
