Online Q&A community provides a platform to create and share knowledge by posting and answering questions. Soliciting information from Q&A thus offers an alternative approach for firms to understand their consumers. This paper proposes an innovative approach to extract consumer preferences based on the online Q&A information. We develop a framework to conduct the analysis and employ Latent Dirichlet Allocation (LDA) algorithm to distill and cluster topics. Based on Zhihu, the most popular online Q&A community in China, we collect almost 50000 answers under the discussion topics of “iPhone 7” and “iPhone X”. We find that our approach can effectively extract and rank consumer preferences to the product. In addition, we find those preferences are inter-related.
Liu, Guan; Wei, Ying; and Li, Feng, "Understanding Consumer Preferences---Eliciting Topics from Online Q&A Community" (2018). ICEB 2018 Proceedings. 30.