Second, sentiment classification systems are typically domain-specific, which makes the expensive process of annotating a large amount of data for each domain and is a bottleneck in building high quality systems<cite> (Dasgupta and Ng, 2009</cite> ). This motivates the task of learning robust sentiment models from minimal supervision (Li, et al., 2009) .