Designing a ranking system for purchased products based on the consumer’s and expert’s opinions using an aspect-based sentiment analysis approach

With the expansion of online sales sites, the desire to online shopping is increasing day by day due to its many benefits. Most customers, before deciding and choosing a product, check the previous buyers of the product opinions and choose their product based on it. There are different brands in the market and on the other hand reviewing a large volume of comments to make a decision to buy a product is a big challenge, the existence of automated text mining and sentiment analysis tools to review users' comments and opinions can be very useful and can be used as a way to rank products based on customer feedback. In this research, by examining more than 4500 customers and experts reviews about 70 products, the features considered by customers and sales site specialists have been extracted based on text mining methods, and by using aspect-based sentiment analysis, a product ranking system has been created.