Evaluate Digital Products Using Emotion Analysis in Web-Based Content

Nowadays, the opinion of users, consumers and customers, in addition to business owners, is very necessary, important and useful for manufacturers, suppliers, marketers and, most importantly, to attract new customers. But analyzing all the opinions and understanding the feelings of previous experts to judge, evaluate, choose the right product by a customer is a very time consuming and difficult task. On the other hand, business owners need tools to understand the feelings of their customers. Therefore, in this study, the analysis of consumers' emotions based on the Platchik emotional model has been considered. Among the methods available in the world of information technology and past research, the use of text mining, machine learning and neural network-based models Emotion Analysis Deep Neural NetworkShort-Long Memory Platchik Emotional Model Support Vector Machine including deep learning, has provided better results. In this research, a machine-based method has been used. This data set has been prepared by designing the site and emotion analysis by volunteers, and the generated data has entered the machine learning phase using a neural network after the pre-processing stages. The results, has been able to make accurate predictions with more than 75% accuracy.