Extracting Customer Intelligence by Social Media Dialog Mining: An Ontology-based Approach for Customer Experience Analysis

This paper provides an ontology-based approach to extract customer intelligence from the unstructured social media dialog data. A UK telecoms company’s Twitter webcare was selected as a case study. The resources and activities of the company and customers in the app using experience were examined following the proposed ontology. We used text mining techniques to do automatic information extraction in the social media dialogs. The results show that customers have positive attitudes towards the service activities such as mobile transaction, special offers via app, yet negative attitudes towards telecoms services via app. The proposed ontology has practical contributes to analyze social media dialogs and develop a relational database for customer intelligence management.