Among methods that use unsupervised learning, Ritter, Cherry, and Dolan (2010) propose two HMM-based unsupervised conversational models for modeling speech acts in Twitter.
they use a simple HMM and a HMM+Topic model to cluster the Twitter posts (not the sentences) into act types.