Analysis of Effective Application of Information Extraction Method for Online Product Reviews Based on User Experience
Jinglin He · 2021 IEEE 2nd International Conference on Information Technology, Big Data and Artificial Intelligence (ICIBA) · 2021
Aiming at product design improvement, a collection and analysis method of user experience information in online product reviews was proposed.First, an user experience element model was constructed.Then, according to the element model, the user emotion, product feature and usage context in a single review sentence were extracted step by step. Finally, the user experience elements extracted from a single review sentence were classified and integrated, and through quantitative analysis of the review data, the product features and use contexts that have a greater impact on user experience were identified. The method was verified by taking the online reviews of a smart phone on Jingdong-Mall as the example. The experimental results show that the method can effectively extract the user experience elements from online product reviews, identify the product features and use contexts that have a great impact on the user experience, and assist designers to improve the product design.