The Quality Attribute Workshop (QAW) is a facilitated method of engaging stakeholders to discover driving quality attributes (QAs). To avoid missing important QAs, we would need to have all stakeholders in the QAW. For Samsung, a consumer electronics maker, consumers are our crucial stakeholders, but we could not invite them all to our QAW in the product-development phase. To mitigate the risk of not having the customers in our QAW, we introduced the social-listening technique to our QAW method and built a data analysis system for a social network service. Our system gathers Twitter users' tweets, analyzes them, and generates reports on keywords related to our products. Instead of hearing from real customers in person, we could hear their voices through Twitter very efficiently and turn them into significant QAs. We could not only identify the QAs that customers are most interested in but also capture new QAs that were not elicited by QAW participants. In this presentation, we present our system's details and real project data to discuss the strengths and weaknesses of our QAW combined with the social-listening method.