Intelligent Method of a Competitive Product Choosing based on the Emotional Feedbacks Coloring

Finding the best products for sale is one of the most important steps in the process of a profitable company creating. That is why the choice of goods for the online store must be made carefully, taking into account both the opportunities and analysis of prospects in the niche, and a number of other important parameters. One of the methods of competitive product choosing can be products analysis in marketplaces based on the emotional feedbacks coloring. Research on product feedbacks is an extremely popular topic, as confirmed by research analysis. Feedbacks can be constantly re-read, but when there are many products in one segment, because there are more and more manufacturers, it is time consuming. Therefore, the development of technology that can automate this process is necessary for the sales business. Paper develops the intelligent method of a competitive product choosing based on the emotional feedbacks coloring, which is divided into three blocks: parser of feedbacks, emotional coloring determination and feedbacks classification. The data will help retailers manage their websites wisely and help customers make purchasing decisions. The implementation of the method was carried out on the data of the Ukrainian site Rozetka, where 4477 feedbacks were used. The classification was tested by eight classical machinebased classification methods, namely Support Vector Classifier, Stochastic Gradient Decent Classifier, Random Forest Classifier, Decision Tree Classifier, Gaussian Naive Bayes, KNeighbors Classifier, Ada Boost Classifier, Logistic Regression.