  With the emerging of various online video platforms like Youtube, Youku and
LeTV, online TV series' reviews become more and more important both for viewers
and producers. Customers rely heavily on these reviews before selecting TV
series, while producers use them to improve the quality. As a result,
automatically classifying reviews according to different requirements evolves
as a popular research topic and is essential in our daily life. In this paper,
we focused on reviews of hot TV series in China and successfully trained
generic classifiers based on eight predefined categories. The experimental
results showed promising performance and effectiveness of its generalization to
different TV series.
