Abstract: With the development of information technology, traditional media is making transformation to the "New Media", which is based on the Internet. Meanwhile, data mining and natural language processing have been developed greatly these years. These technologies are utilized to uncover the semantics and topics in news articles. In addition, the overflow of information motivates the development of new visualization methods. Overall, these methods have great potential of making people better understand news. LDA is a promising topic modeling method, which is adopted by lots of researchers. In this paper, we first introduced the text probabilistic topic modeling technologies based on LDA and discussed the unique characteristics of topic modeling for news. Then, we summarized different visualization methods of topic modeling for news. We also analyzed and compared advantages and shortcomings of these methods. At last, we discussed some future directions of topic modeling for news.