Classified Recognition Method for Analyzing User Sentiments Using Social Media Posts

Social media texts and posts are analyzed through modern computing and artificial intelligence systems to detect user sentiments. The severity of the words and their related activities are analyzed to detect the user sentiments. In this paper, a Classified Sentiment Recognition Method (CSRM) is introduced. The proposed method utilizes deep learning to identify and classify sentiments using their associated words. Using the associated labels, deep learning trains the context and occurrence of the texts/ posts to detect precise sentiments. Thus the learning steps are induced with label, context, and occurrence-based training to improve the sentiment detection and type classification. This proposed method is verified using recognition accuracy, classification rate, and recognition error.