Mining Customer Experience on the Web 2.0

Abstract

In the course of the social orientation of the internet there is an increasing number of customers who are sharing their product experiences. The growing web 2.0 holds a valuable source of knowledge for companies. However, the manual analysis of customer experience in the web 2.0 is very time consuming. This paper proposes a system which allows an automatic analysis of customer experience by using methods from text mining and data mining. The system enables the extraction, aggregation and analysis of product features and their evaluations. Thus valuable information for product development and improvement can be gained.