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.