A social media mining framework for quality determinant identifying using text mining and decision tree

Identifying quality determinants is crucial across various fields, such as healthcare, manufacturing, education, and services, for several reasons including improved outcomes, and enhanced customer satisfaction. Among the various methods of identifying quality determinants, text mining of social media provides valuable insights regarding quality determinants, helping businesses refine their strategies, improve customer satisfaction, and maintain a competitive edge. By leveraging these techniques, organizations can create a more responsive and quality-focused approach to their products and services. Combining text mining with other data mining methods can lead to more clear results. Among these data mining methods, we can mention the Decision Tree for data classification. More precisely, a Decision Tree can identify the relationship between factors affecting quality and customer satisfaction in the form of a set of rules. In this article, a new framework that includes text mining and the Decision Tree (C5.0) is proposed to identify quality determinants. The proposed In social media mining framework has been implemented on the data collected from the Twitter social network regarding “car” product and its results have been extracted in the form of valid rules. These rules can be used to determine the most important features affecting the satisfaction or dissatisfaction of customers with the studied product.