Product selection based on sentiment analysis of online reviews: an intuitionistic fuzzy TODIM method

Online reviews contain a great deal of information about consumers' purchasing preferences, which seriously affects potential consumers' purchasing decisions. Using the online review data to help customers make purchasing decisions has become a concern of customers, which has theoretical and practical application value. Therefore, a product selection model is presented based on sentiment analysis combined with an intuitionistic fuzzy TODIM method. Firstly, the product features are extracted by the Apriori algorithm based on online reviews. The sentiment orientation and intensity of the sentiment words for the product features are identified by the lexicon-based sentiment analysis approach. Next, the sentiment orientation of the product features is represented by an intuitionistic fuzzy value. Then the intuitionistic fuzzy TODIM method is used to determine the ranking results of the alternative products. Finally, the case study of mobile phone selection is given to illustrate the proposed approach. The results show that the proposed method considers the online reviews' sentiment orientation and intensity and the consumers' gain and loss in the purchasing product process and is more reasonable than the previous research.

Automated summary

This article presents a product selection model based on sentiment analysis and intuitionistic fuzzy TODIM method, which helps consumers make more reasonable purchasing decisions by extracting product features and sentiment orientation from online reviews.