  In recent years, voice knowledge sharing and question answering (Q&A)
platforms have attracted much attention, which greatly facilitate the knowledge
acquisition for people. However, little research has evaluated on the quality
evaluation on voice knowledge sharing. This paper presents a data-driven
approach to automatically evaluate the quality of a specific Q&A platform
(Zhihu Live). Extensive experiments demonstrate the effectiveness of the
proposed method. Furthermore, we introduce a dataset of Zhihu Live as an open
resource for researchers in related areas. This dataset will facilitate the
development of new methods on knowledge sharing services quality evaluation.
