Another recently proposed non-negative matrix tri-factorization approach (Li et al., 2009) also employed lexical prior knowledge for semi-supervised sentiment classification.
when incorporating 10% of labelled documents for training, the non-negative matrix tri-factorization approach performed much worse than LSM, with only around 60% accuracy achieved for all the datasets.