Summarizing and analyzing Twitter content is an important and challenging task. In this paper, we propose to extract topical keyphrases as one way to summarize Twitter. We propose a context-sensitive topical PageRank for keyword ranking and probabilistic scoring function that considers both relevance and interestingness of keyphrases for keyphrase ranking. We evalaute our proposed methods in a large Twitter data set. Experiments show that these methods are very effective for topical keyphrase extraction.